Data Science For Beginners
Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science.
In 4 listsDetails
Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science.
AWESOME DATA SCIENCE
:memo: An awesome Data Science repository to learn and apply for real world problems.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
What is Data Science?
What is Data Science @ O'reilly
Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data…
What is Data Science @ Quora
Data Science is a combination of a number of aspects of Data such as Technology, Algorithm development, and data interference to study the data, analyse it, and find innovative solutions to difficult problems. Basically Data Science is all about Analysing data and driving for business growth by…
The sexiest job of 21st century
Data scientists today are akin to Wall Street “quants” of the 1980s and 1990s. In those days people with backgrounds in physics and math streamed to investment banks and hedge funds, where they could devise entirely new algorithms and data strategies. Then a variety of universities developed…
Wikipedia
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
How to Become a Data Scientist
Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyze, process, and model data then interpret the results to create actionable plans for companies…
a very short history of #datascience
The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one--computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast…
Software Development Resources for Data Scientists
Data scientists concentrate on making sense of data through exploratory analysis, statistics, and models. Software developers apply a separate set of knowledge with different tools. Although their focus may seem unrelated, data science teams can benefit from adopting software development best…
Data Scientist Roadmap
Data science is an excellent career choice in today’s data-driven world where approx 328.77 million terabytes of data are generated daily. And this number is only increasing day by day, which in turn increases the demand for skilled data scientists who can utilize this data to drive business growth.
Navigating Your Path to Becoming a Data Scientist
_Data science is one of the most in-demand careers today. With businesses increasingly relying on data to make decisions, the need for skilled data scientists has grown rapidly. Whether it’s tech companies, healthcare organizations, or even government institutions, data scientists play a crucial…
Where do I Start?
Python
is by far the most popular language in science, due in no small part to the ease at which it can be used and the vibrant ecosystem of user-generated packages. To install packages, there are two main methods: Pip (invoked as pip install), the package manager that comes bundled with Python, and…
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Agents >Frameworks
ADK-Rust
Production-ready AI agent development kit for Rust with model-agnostic design (Gemini, OpenAI, Anthropic), multiple agent types (LLM, Graph, Workflow), MCP support, and built-in telemetry.
Lumen
Agent framework for chatting with data, turning natural language into SQL, transformation pipelines and visualizations. Outputs are declarative specs that can be inspected, edited, reopened in a notebook or composed into a dashboard.
Agents >Tools
Frostbyte MCP
MCP server providing 13 data tools for AI agents: real-time crypto prices, IP geolocation, DNS lookups, web scraping to markdown, code execution, and screenshots. One API key for 40+ services.
Arch Tools
61 production-ready AI API tools for data science workflows: code analysis, web scraping, NLP, image generation, crypto data, and search. REST API and MCP protocol support. GitHub
Not Human Search
Search engine for AI agents that indexes 9,000+ AI tools and APIs, scoring each on agentic readiness (llms.txt, OpenAPI, MCP, ai-plugin.json). REST API and MCP server for programmatic tool discovery. GitHub
In 4 listsDetails
DeepAlpha
AI crypto trading framework using LightGBM + XGBoost ensemble with 72 ML features. 70.9% walk-forward validated accuracy on out-of-sample data. Supports Bybit and Binance. MIT licensed, available on PyPI.
In 3 lists
CAJAL
Local AI agent for generating publication-ready scientific papers with real arXiv citations, IMRaD structure, and tribunal scoring. Runs 100% offline via Ollama with 4B-9B models. MIT licensed. HuggingFace
ai-evaluation
Open-source LLM and agent evaluation framework with 50+ metrics, LLM-as-Judge augmentation, and guardrail scanners (jailbreak, PII, prompt-injection). Useful for scoring RAG outputs, agent trajectories, and function-calling behavior in data-science workflows.
In 2 lists
Kitaru
Open-source platform that records real AI agent runs, replays them against changes, and evaluates outcomes before deployment.
In 2 lists
Jev Social
Read-only social research agent that lets Jev choose bounded Instagram, TikTok, and LinkedIn operations, runs them through the local socai CLI in Chrome, and preserves source-linked evidence beside a cited report.
In 8 listsDetails
YYLO Benchmark
Open-source trusted-host experiment runner for historical agent tasks, supplied coding prompts, and workflows. Runs independent attempts with retained outputs, and compares models, harnesses, and configurations with different checks or judges later. MIT licensed.
In 2 lists
Agents >Research & Knowledge Retrieval
BGPT MCP
MCP server that gives AI agents access to a database of scientific papers built from raw experimental data extracted from full-text studies. Returns 25+ structured fields per paper including methods, results, sample sizes, and quality scores. GitHub
In 2 lists
Chunk Tuner
Open-source Python library and MCP server to benchmark document chunking strategies for RAG, score retrieval quality, and recommend configurations for a corpus.
II-Commons
Daily-updated skill and CLI for deterministic retrieval across arXiv, PubMed/PMC, and supported US policy corpora.
In 3 lists
Spraay x402 Gateway
x402 payment gateway with 23 Research & Reference endpoints for AI agents: Wikipedia, arXiv, PubMed, Wikidata, academic citation lookup, entity extraction, and more. Pay-per-call in USDC on Base & Solana — no API keys or subscriptions. Also serves 150+ endpoints across 39 categories including…
Suppr
AI literature search, document translation, and deep-research workspace for researchers.
Agents >Workflow
sim
Sim Studio's interface is a lightweight, intuitive way to quickly build and deploy LLMs that connect with your favorite tools.
Projects
Synthetic Hospital
A Medical Benchmark & EHR Simulation Platform
Training Resources >Tutorials
1000 Data Science Projects
you can run on the browser with IPython.
#tidytuesday
A weekly data project aimed at the R ecosystem.
In 3 lists
DataCamp Cheatsheets
Cheatsheets for data science.
PySpark Cheatsheet
Common PySpark patterns.
In 2 lists
Machine Learning, Data Science and Deep Learning with Python
LiveVideo tutorial that covers machine learning, Tensorflow, artificial intelligence, and neural networks.
In 3 lists
TutorialSearch
Free cross-platform search engine indexing 50,000+ tutorials from Udemy, Skillshare, Pluralsight, and other major learning platforms across 45+ categories.
In 2 lists
Realtime deployment
Tutorial on Python time-series model deployment.
Best CV/Resume for Data Science Freshers
A collection of resume examples and tips tailored for data scientists.
In 2 lists
DataDriven - SQL, Python, and Data Modeling Interview Questions
Interview practice with SQL query execution, Python, and data modeling exercises.
In 2 lists
StepByStepML
Interactive calculator that visualizes the step-by-step manual math behind machine learning algorithms for exam prep.
How to Build Optimal AI Agents That Actually Work
A developer handbook on designing and building effective AI agents.
Train LLM From Scratch
A straightforward method for training your LLM, from downloading data to generating text.
In 2 lists
Training Resources >Free Courses
Data Science
Open Source Society University
In 3 lists
AI Expert Roadmap
Roadmap to becoming an Artificial Intelligence Expert
In 4 listsDetails
Convex Optimization
Convex Optimization (basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory...)
Learning from Data
Introduction to machine learning covering basic theory, algorithms and applications
Kaggle
Learn about Data Science, Machine Learning, Python etc
In 2 lists
ML Observability Fundamentals
Learn how to monitor and root-cause production ML issues.
Weights & Biases Effective MLOps: Model Development
Free Course and Certification for building an end-to-end machine using W&B
Python for Data Science by Scaler
This course is designed to empower beginners with the essential skills to excel in today's data-driven world. The comprehensive curriculum will give you a solid foundation in statistics, programming, data visualization, and machine learning.
MLSys-NYU-2022
Slides, scripts and materials for the Machine Learning in Finance course at NYU Tandon, 2022.
In 2 lists
Hands-on Train and Deploy ML
A hands-on course to train and deploy a serverless API that predicts crypto prices.
In 2 lists
LLMOps: Building Real-World Applications With Large Language Models
Learn to build modern software with LLMs using the newest tools and techniques in the field.
In 2 lists
Prompt Engineering for Vision Models
Learn to prompt cutting-edge computer vision models with natural language, coordinate points, bounding boxes, segmentation masks, and even other images in this free course from DeepLearning.AI.
In 3 lists
Data Science Course By IBM
Free resources and learn what data science is and how it’s used in different industries.
Neural Networks: Zero to Hero
A free video series by Andrej Karpathy covering neural networks from scratch — backpropagation, makemore, GPT, and more.
In 3 lists
Training Resources >MOOC's
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Oxford Deep Learning - video
, Video Lectures Summer School Montreal
In 3 lists
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Coursera Big Data Specialization
30 weeks
In 2 lists
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CS 231 - Convolutional Neural Networks for Visual Recognition
Fei-Fei Li, Andrej Karphaty, Justin Johnson (Stanford University)
In 2 lists
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Coursera Deep Learning Specialization
New series of 5 Deep Learning courses by Andrew Ng, now with Python rather than Matlab/Octave, and which leads to a specialization certificate.
In 6 listsDetails
Coursera Natural Language Processing Specialization
Teaches how to use machine learning to understand and manipulate human language. It requires a working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & statistics.
In 3 lists
Codecademy's Data Science
Interactive courses for learning data analysis.
In 2 lists
Linear Algebra
Linear Algebra course by Gilbert Strang
Recommender Systems Specialization from University of Minnesota
is an intermediate/advanced level specialization focused on Recommender System on the Coursera platform.
Introduction to Data Science
Getting Started with Python for Data Science
Google Advanced Data Analytics Certificate
Professional courses in data analysis, statistics, and machine learning fundamentals.
Maschinelle Sprachgebrauchsanalyse - Grundlagen der Korpuslinguistik
course material on text-mining / corpus-linguistics in German funded by the federal state of North Rhine-Westphalia
Programmieren für Germanist*innen
course material: programming in python in German for digital humanities - funded by the federal state of North Rhine-Westphalia
QuiddityML
Short lessons with hands-on coding exercises and spaced repetition, covering Python, PyTorch, math for ML, ML foundations, NLP, and computer vision.
In 3 lists
Training Resources >Intensive Programs
Great Learning Data Science Programs
A collection of online data science and analytics certificate, postgraduate, and degree programs.
Training Resources >Colleges
The Data Science Toolbox >Comparison
Linear Regression
is an approach to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
In 3 lists
Logistic Regression
Easily plottable and understandable classification.
In 3 lists
k-nearest neighbor
The prototypical clustering method.
In 2 lists
Decision Trees
The tree provides an interpretation.
In 3 lists
In 2 lists
AdaBoost
, Python Code
In 2 lists
Clustering
scikit-learn clustering algorithms.
In 2 lists
Naive Bayes
is a machine learning algorithm that is used solved calssification problems. It's based on applying Bayes' theorem with strong independence assumptions between the features.
In 4 listsDetails
CatBoost
is a fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
In 3 lists
The Data Science Toolbox >General Machine Learning Packages
scikit-learn
A Python module for machine learning built on top of SciPy.
In 3 lists
scikit-multilearn
Multi-label classification for python.
In 3 lists
sklearn-expertsys
Highly interpretable classifiers for scikit learn.
In 2 lists
scikit-feature
Feature selection repository in Python.
In 2 lists
scikit-rebate
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
In 2 lists
seqlearn
Sequence classification toolkit for Python.
In 2 lists
sklearn-bayes
Python package for Bayesian Machine Learning with scikit-learn API.
In 3 lists
sklearn-crfsuite
A scikit-learn-inspired API for CRFsuite.
In 2 lists
sklearn-deap
Use evolutionary algorithms instead of gridsearch in scikit-learn.
In 2 lists
sklearn-evaluation
Model evaluation made easy: plots, tables, and markdown reports.
In 2 lists
scikit-image
A collection of algorithms for image processing in Python.
In 6 listsDetails
scikit-opt
Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm, Artificial Fish Swarm Algorithm in Python)
In 3 lists
scikit-posthocs
Post-hoc tests for statistical analysis of data.
In 3 lists
me_fasttext
Memory-efficient FastText variant with exact trie n-gram IDs, structure-aware row sharing, and mmap serving for large-vocabulary NLP.
pystruct
Simple structured learning framework for Python.
In 2 lists
xLearn
A high performance, easy-to-use, and scalable machine learning package, which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data, which is very common in Internet services such as online…
In 3 lists
cuML
is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the…
In 7 listsDetails
causalml
Uplift modeling and causal inference with machine learning algorithms.
In 2 lists
MLxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
In 4 listsDetails
Sparkit-learn
PySpark + scikit-learn = Sparkit-learn.
In 2 lists
hyperlearn
50%+ Faster, 50%+ less RAM usage, GPU support re-written Sklearn, Statsmodels.
In 2 lists
dlib
zap: - A toolkit for making real world machine learning and data analysis applications in C++. [Boost] website
In 7 listsDetails
jSciPy
A Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.
In 3 lists
RuleFit
Implementation of the rulefit.
In 2 lists
pyGAM
A Python library for generalized additive models with built-in smoothing and regularization.
In 3 lists
Deepchecks
Validation & testing of machine learning models and data during model development, deployment, and production. This includes checks and suites related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.
In 8 listsDetails
XGBoost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow. [Apache2]
In 11 listsDetails
LightGBM
Microsoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
In 8 listsDetails
CatBoost
General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
In 10 listsDetails
PerpetualBooster
A gradient boosting machine that doesn't need hyperparameter optimization, with a simple budget parameter to control model complexity.
In 3 lists
JAX
| Python | - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
In 6 listsDetails
PhilanthroPy
Scikit-learn native toolkit for nonprofit fundraising analytics: leakage-safe donor propensity, lapse, planned-giving, wealth-screening and revenue-forecasting estimators.
In 2 lists
The Data Science Toolbox >Deep Learning Packages
PyTorch
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
In 16 listsDetails
TorchDR
GPU and multi-GPU dimensionality reduction with a scikit-learn-compatible API.
In 2 lists
torchvision
PyTorch's official computer vision library with 50+ pre-trained model architectures including ResNet, EfficientNet, Vision Transformers (ViT), ConvNeXt, and more. The de facto standard model zoo for PyTorch computer vision. BSD-3-Clause licensed.
In 9 listsDetails
torchtext
：Torchtext是一个非常好用的库，可以帮助我们很好的解决文本的预处理问题。此github存储库包含两部分：; torchText.data：文本的通用数据加载器、抽象和迭代器（包括词汇和词向量）; torchText.datasets：通用NLP数据集的预训练加载程序 我们只需要通过pip install torchtext安装好torchtext后，便可以开始体验Torchtext 的种种便捷之处。
In 4 listsDetails
torchaudio
A set of tools and building blocks for audio and speech processing, designed to accelerate the development and deployment of machine learning applications in these domains. It offers GPU-compatible, differentiable, and production-ready components, making it valuable for integrating audio…
In 6 listsDetails
ignite
High-level library for training and evaluating neural networks in PyTorch with an engine, events & handlers system for maximum flexibility. BSD-3-Clause licensed.
In 7 listsDetails
PyToune
A Keras-like framework for PyTorch that handles much of the boilerplating code needed to train neural networks.
In 2 lists
skorch
scikit-learn compatible neural network library that wraps PyTorch. Seamlessly integrate PyTorch models with scikit-learn pipelines, grid search, and cross-validation.
In 5 listsDetails
PyVarInf
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch.
In 3 lists
pytorch_geometric
Graph neural network library for PyTorch enabling molecular modeling, materials discovery, protein interaction networks, and scientific knowledge graph learning (23.7k+ stars)
In 7 listsDetails
GPyTorch
A highly efficient and modular implementation of Gaussian Processes in PyTorch.
In 3 lists
pyro
Deep universal probabilistic programming with Python and PyTorch.
In 3 lists
Catalyst
High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing. Being able to research/develop something new, rather than write another regular train loop.
In 6 listsDetails
Yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
In 3 lists
Yolov5
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
In 3 lists
Yolov8
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
In 6 listsDetails
OpenLanguageModel
PyTorch-native library for building, training and teaching transformer language models, with architectures written as ordinary nn.Modules.
TensorFlow
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.
In 23 listsDetails
TensorLayer
Deep learning and reinforcement learning library for researchers and engineers
In 3 lists
Sonnet
Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.
In 6 listsDetails
TRFL
TensorFlow Reinforcement Learning.
In 2 lists
Polyaxon
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle. Reproducible and scalable machine learning workflows on Kubernetes with experiment tracking, model management, and pipeline orchestration. Apache 2.0 licensed.
In 9 listsDetails
tfdeploy
Deploy TensorFlow graphs for fast evaluation and export to TensorFlow-less environments running numpy.
In 2 lists
tensorflow-upstream
TensorFlow ROCm port.
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TensorFlow Fold
Deep learning with dynamic computation graphs in TensorFlow.
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TensorLight
A high-level framework for TensorFlow.
In 2 lists
Mesh TensorFlow
Model Parallelism Made Easier.
In 2 lists
Ludwig
Low-code framework for building custom LLMs and deep neural networks. Declarative YAML configuration for training state-of-the-art models with PEFT/LoRA, 4-bit quantization, distributed training via Hugging Face Accelerate, and native Kubernetes support. Linux Foundation AI project. Apache 2.0…
In 6 listsDetails
TF-Agents
A reliable, scalable and easy to use TensorFlow library for contextual bandits and reinforcement learning.
In 4 listsDetails
TensorForce
An open-source deep reinforcement learning framework, with an emphasis on modularized flexible library design and straightforward usability for applications in research and practice.
In 2 lists
Keras
Neural Networks on top of tensorflow, examples. keras-contrib - Keras community contributions. keras-tuner - Hyperparameter tuning for Keras. hyperas - Keras + Hyperopt: Convenient hyperparameter optimization wrapper. elephas - Distributed Deep learning with Keras & Spark. tflearn - Neural…
In 8 listsDetails
keras-contrib
Keras community contributions.
In 2 lists
Hyperas
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization.
In 4 listsDetails
Elephas
Distributed Deep learning with Keras & Spark.
In 3 lists
Spektral
Deep learning on graphs.
In 2 lists
qkeras
A quantization deep learning library.
In 2 lists
keras-rl
Deep Reinforcement Learning for Keras.
In 2 lists
Talos
Hyperparameter Optimization for TensorFlow, Keras and PyTorch.
In 3 lists
altair
Declarative statistical visualization library for Python. Can easily do many data transformation within the code to create graph
In 3 lists
amcharts
Three libraries for traditional charts, stock, and maps. Features a hand-drawn style theme option.
In 3 lists
anychart
AnyChart Component for Ember CLI provides an easy way to use AnyChart JavaScript Charts with Ember Framework
In 3 lists
bokeh
Python library for interactive data visualization in the browser, with support for networks.
In 2 lists
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d3plus
D3's simpler, easier to use cousin. Mostly predefined templates that you can just plug data in.
In 2 lists
Data-Driven Documents(D3js)
Allows the user to manipulate documents based on data to render charts in SVG.
In 9 listsDetails
dygraphs
Interactive line charts library that works with huge datasets.
In 3 lists
In 2 lists
gephi
Leading visualization and exploration software for all kinds of graphs and networks.
In 6 listsDetails
ggplot2
Resource for plotting a wide range of data (useful for visualizing survey data). Additional Information: GNU GENERAL PUBLIC LICENSE.
In 4 listsDetails
Highcharts
A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application.
In 6 listsDetails
In 3 lists
Matplotlib
is a 2D plotting library for creating static, animated, and interactive visualizations in Python. Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.
In 4 listsDetails
Netron
Visualizer for deep learning and machine learning models (no Python code, but visualizes models from most Python Deep Learning frameworks).
In 15 listsDetails
plot.ly
Easy-to-use web service that allows for rapid creation of complex charts, from heatmaps to histograms. Upload data to create and style charts with Plotly's online spreadsheet. Fork others' plots.
In 4 listsDetails
raw
SVG Data Visualization Generator - sunburst, circular dendrogram or multiple convex hull, for example. with tutorials: https://rawgraphs.io/learning
In 5 listsDetails
Seaborn
A Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
In 6 listsDetails
techanjs
Stock and financial charts.
In 2 lists
vizzu
Library for animated data visualizations and data stories.
In 3 lists
NetworkX
Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
In 2 lists
Redash
"Redash has support for querying multiple databases, including: Redshift, Google BigQuery, PostgreSQL, MySQL, Graphite, Presto, Google Spreadsheets, Cloudera Impala, Hive and custom scripts."
In 6 listsDetails
Metabase
Easy way for everyone in your company to ask questions and learn from data. (Source Code) AGPL-3.0 Java/Docker
In 8 listsDetails
TensorWatch
Debugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training.
In 5 listsDetails
Dash
is a popular Python framework for building ML & data science web apps for Python, R, Julia, and Jupyter.
In 2 lists
MetaReview
Free online meta-analysis platform with 11 interactive D3.js statistical charts (forest plot, funnel plot, Galbraith, L'Abbé, Baujat, etc.), 5 effect size measures, AI literature screening, and publication-ready report export. github.com
torchvista
Interactive notebook-based tool to visualize the forward pass of any PyTorch model.
In 3 lists
The Data Science Toolbox >Miscellaneous Tools
The Data Science Lifecycle Process
The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo
Data Science Lifecycle Template Repo
Template repository for data science lifecycle project
TabGAN
Synthetic tabular data generation using GANs, Diffusion Models, and LLMs with adversarial filtering and privacy metrics.
In 2 lists
RexMex
A general purpose recommender metrics library for fair evaluation.
In 2 lists
ChemicalX
A PyTorch based deep learning library for drug pair scoring.
In 3 lists
FileShot.io
Secure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
In 3 lists
CorpusExplorer
Software for corpus linguists and text/data mining enthusiasts. Build your own corpora in over 60 languages. Use over 50 tools/visualizations.
In 2 lists
PyTorch Geometric Temporal
Representation learning on dynamic graphs.
In 5 listsDetails
Little Ball of Fur
A graph sampling library for NetworkX with a Scikit-Learn like API.
In 5 listsDetails
Karate Club
An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.
In 7 listsDetails
ML Workspace
All-in-one web-based IDE for machine learning and data science. The workspace is deployed as a Docker container and is preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch) and dev tools (e.g., Jupyter, VS Code)
In 10 listsDetails
xonsh shell
A Python-powered shell that enables integration, management and orchestration of data science libraries mostly written in Python, allowing you to build pipelines, code and command-based workflows. It can also be used as a kernel for Jupyter Notebook.
In 4 listsDetails
Neptune.ai
Community-friendly platform supporting data scientists in creating and sharing machine learning models. Neptune facilitates teamwork, infrastructure management, models comparison and reproducibility.
In 6 listsDetails
steppy
Lightweight, Python library for fast and reproducible machine learning experimentation. Introduces very simple interface that enables clean machine learning pipeline design.
In 2 lists
steppy-toolkit
Curated collection of the neural networks, transformers and models that make your machine learning work faster and more effective.
Datalab from Google
easily explore, visualize, analyze, and transform data using familiar languages, such as Python and SQL, interactively.
Hortonworks Sandbox
is a personal, portable Hadoop environment that comes with a dozen interactive Hadoop tutorials.
R
is a free software environment for statistical computing and graphics.
In 2 lists
Tidyverse
is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.
RStudio
IDE – powerful user interface for R. It’s free and open source, and works on Windows, Mac, and Linux.
In 7 listsDetails
Python - Pandas - Anaconda
Completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing
In 4 listsDetails
Pandas GUI
Pandas GUI
NuriStat
Free open-source SPSS alternative — menu-driven desktop statistics (t-tests, ANOVA, regression, survival analysis, ROC) with SPSS .sav import/export
Polars
Fast DataFrame library for Rust and Python, designed as a faster alternative to Pandas
In 10 listsDetails
CiteMe
free academic citation generator with a built-in reference checker that flags fabricated or hallucinated references. Searches 11+ scholarly databases (OpenAlex, PubMed, Semantic Scholar, CrossRef, SciELO), formats 40+ citation styles, and offers a public API. No sign-up; available in English,…
In 2 lists
Scikit-Learn
Machine Learning in Python
In 5 listsDetails
NumPy
NumPy is fundamental for scientific computing with Python. It supports large, multi-dimensional arrays and matrices and includes an assortment of high-level mathematical functions to operate on these arrays.
In 7 listsDetails
Vaex
Vaex is a Python library that allows you to visualize large datasets and calculate statistics at high speeds.
SciPy
SciPy works with NumPy arrays and provides efficient routines for numerical integration and optimization.
In 7 listsDetails
Data Science Toolbox
Coursera Course
Wolfram Data Science Platform
Take numerical, textual, image, GIS or other data and give it the Wolfram treatment, carrying out a full spectrum of data science analysis and visualization and automatically generate rich interactive reports—all powered by the revolutionary knowledge-based Wolfram Language.
Kite Development Kit
The Kite Software Development Kit (Apache License, Version 2.0), or Kite for short, is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem.
Domino Data Labs
Run, scale, share, and deploy your models — without any infrastructure or setup.
In 4 listsDetails
Apache Flink
A platform for efficient, distributed, general-purpose data processing.
In 6 listsDetails
Apache Hama
Apache Hama is an Apache Top-Level open source project, allowing you to do advanced analytics beyond MapReduce.
Weka
Weka is a collection of machine learning algorithms for data mining tasks.
Octave
GNU Octave is a high-level interpreted language, primarily intended for numerical computations.(Free Matlab)
In 6 listsDetails
Apache Spark
Lightning-fast cluster computing
In 7 listsDetails
Hydrosphere Mist
a service for exposing Apache Spark analytics jobs and machine learning models as realtime, batch or reactive web services.
In 3 lists
Data Mechanics
A data science and engineering platform making Apache Spark more developer-friendly and cost-effective.
In 2 lists
Caffe
Deep Learning Framework
Torch
A SCIENTIFIC COMPUTING FRAMEWORK FOR LUAJIT
Nervana's python based Deep Learning Framework
Intel® Nervana™ reference deep learning framework committed to best performance on all hardware.
In 4 listsDetails
Skale
High performance distributed data processing in NodeJS
Aerosolve
A machine learning package built for humans.
Intel framework
Intel® Deep Learning Framework
Datawrapper
An open source data visualization platform helping everyone to create simple, correct and embeddable charts. Also at github.com
In 2 lists
Tensor Flow
TensorFlow is an Open Source Software Library for Machine Intelligence
In 5 listsDetails
Natural Language Toolkit
An introductory yet powerful toolkit for natural language processing and classification
In 4 listsDetails
FunASR
Industrial-grade speech recognition toolkit supporting 50+ languages with built-in VAD, punctuation, speaker diarization, and emotion detection. OpenAI-compatible API server included.
In 9 listsDetails
Annotation Lab
Free End-to-End No-Code platform for text annotation and DL model training/tuning. Out-of-the-box support for Named Entity Recognition, Classification, Relation extraction and Assertion Status Spark NLP models. Unlimited support for users, teams, projects, documents.
In 2 lists
nlp-toolkit for node.js
This module covers some basic nlp principles and implementations. The main focus is performance. When we deal with sample or training data in nlp, we quickly run out of memory. Therefore every implementation in this module is written as stream to only hold that data in memory that is currently…
Julia
high-level, high-performance dynamic programming language for technical computing
In 5 listsDetails
IJulia
a Julia-language backend combined with the Jupyter interactive environment
Apache Zeppelin
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more
In 4 listsDetails
Featuretools
An open source framework for automated feature engineering written in python
In 6 listsDetails
Optimus
Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
Albumentations
А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, and detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR…
In 3 lists
DVC
An open-source data science version control system. It helps track, organize and make data science projects reproducible. In its very basic scenario it helps version control and share large data and model files.
In 8 listsDetails
Lambdo
is a workflow engine that significantly simplifies data analysis by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation.
In 2 lists
Feast
A feature store for the management, discovery, and access of machine learning features. Feast provides a consistent view of feature data for both model training and model serving.
In 6 listsDetails
Polyaxon
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle. Reproducible and scalable machine learning workflows on Kubernetes with experiment tracking, model management, and pipeline orchestration. Apache 2.0 licensed.
In 9 listsDetails
UBIAI
Easy-to-use text annotation tool for teams with most comprehensive auto-annotation features. Supports NER, relations and document classification as well as OCR annotation for invoice labeling
In 3 lists
Trains
Auto-Magical Experiment Manager, Version Control & DevOps for AI
In 3 lists
Hopsworks
Open-source data-intensive machine learning platform with a feature store. Ingest and manage features for both online (MySQL Cluster) and offline (Apache Hive) access, train and serve models at scale.
In 5 listsDetails
MindsDB
MindsDB is an Explainable AutoML framework for developers. With MindsDB you can build, train and use state of the art ML models in as simple as one line of code.
In 11 listsDetails
Lightwood
A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with an objective to build predictive models with one line of code.
In 2 lists
AWS Data Wrangler
An open-source Python package that extends the power of Pandas library to AWS connecting DataFrames and AWS data related services (Amazon Redshift, AWS Glue, Amazon Athena, Amazon EMR, etc).
In 3 lists
Amazon Rekognition
AWS Rekognition is a service that lets developers working with Amazon Web Services add image analysis to their applications. Catalog assets, automate workflows, and extract meaning from your media and applications.
In 2 lists
Amazon Textract
Automatically extract printed text, handwriting, and data from any document.
In 2 lists
Amazon Lookout for Vision
Spot product defects using computer vision to automate quality inspection. Identify missing product components, vehicle and structure damage, and irregularities for comprehensive quality control.
Amazon CodeGuru
Automate code reviews and optimize application performance with ML-powered recommendations.
In 2 lists
CML
An open source toolkit for using continuous integration in data science projects. Automatically train and test models in production-like environments with GitHub Actions & GitLab CI, and autogenerate visual reports on pull/merge requests.
In 4 listsDetails
Dask
An open source Python library to painlessly transition your analytics code to distributed computing systems (Big Data)
In 3 lists
Statsmodels
A Python-based inferential statistics, hypothesis testing and regression framework
In 3 lists
Gensim
An open-source library for topic modeling of natural language text
In 3 lists
Grid Studio
Grid studio is a web-based spreadsheet application with full integration of the Python programming language.
In 2 lists
Python Data Science Handbook
Python Data Science Handbook: full text in Jupyter Notebooks
In 4 listsDetails
Shapley
A data-driven framework to quantify the value of classifiers in a machine learning ensemble.
In 4 listsDetails
DAGsHub
A platform built on open source tools for data, model and pipeline management.
In 4 listsDetails
Deepnote
A new kind of data science notebook. Jupyter-compatible, with real-time collaboration and running in the cloud.
In 3 lists
Valohai
An MLOps platform that handles machine orchestration, automatic reproducibility and deployment.
In 2 lists
PyMC3
A Python Library for Probabalistic Programming (Bayesian Inference and Machine Learning)
In 2 lists
PyStan
Python interface to Stan (Bayesian inference and modeling)
hmmlearn
Unsupervised learning and inference of Hidden Markov Models
Chaos Genius
ML powered analytics engine for outlier/anomaly detection and root cause analysis
In 5 listsDetails
PySAD
Python library for anomaly detection on streaming data
In 2 lists
Nimblebox
A full-stack MLOps platform designed to help data scientists and machine learning practitioners around the world discover, create, and launch multi-cloud apps from their web browser.
Towhee
A Python library that helps you encode your unstructured data into embeddings.
In 2 lists
LineaPy
Ever been frustrated with cleaning up long, messy Jupyter notebooks? With LineaPy, an open source Python library, it takes as little as two lines of code to transform messy development code into production pipelines.
In 2 lists
envd
🏕️ machine learning development environment for data science and AI/ML engineering teams
In 5 listsDetails
Explore Data Science Libraries
A search engine 🔎 tool to discover & find a curated list of popular & new libraries, top authors, trending project kits, discussions, tutorials & learning resources
cleanlab
Python library for data-centric AI and automatically detecting various issues in ML datasets
In 8 listsDetails
AutoGluon
AutoML to easily produce accurate predictions for image, text, tabular, time-series, and multi-modal data
In 5 listsDetails
Arize AI
Arize AI community tier observability tool for monitoring machine learning models in production and root-causing issues such as data quality and performance drift.
In 3 lists
Aureo.io
Aureo.io is a low-code platform that focuses on building artificial intelligence. It provides users with the capability to create pipelines, automations and integrate them with artificial intelligence models – all with their basic data.
ERD Lab
Free cloud based entity relationship diagram (ERD) tool made for developers.
In 5 listsDetails
Arize-Phoenix
MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.
Comet
An MLOps platform with experiment tracking, model production management, a model registry, and full data lineage to support your ML workflow from training straight through to production.
In 4 listsDetails
Opik
Evaluate, test, and ship LLM applications across your dev and production lifecycles.
In 16 listsDetails
Synthical
AI-powered collaborative environment for research. Find relevant papers, create collections to manage bibliography, and summarize content — all in one place
In 4 listsDetails
teeplot
Workflow tool to automatically organize data visualization output
Weights & Biases
Experiment tracking, dataset versioning, and model management
In 5 listsDetails
Apache Airflow
Platform to programmatically author, schedule, and monitor workflows
In 13 listsDetails
Kedro
Open-source Python framework for creating reproducible, maintainable data science code
In 7 listsDetails
InterpretML
InterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations
In 8 listsDetails
zasper
Supercharged IDE for Data Science
In 3 lists
skrub
A Python library to ease preprocessing and feature engineering for tabular machine learning
In 3 lists
Glyph
Framework-agnostic TypeScript library for generating, searching, and comparing MinHash fingerprints for fast text similarity, deduplication, and retrieval.
In 2 lists
Hugging Face
Popular open platform for sharing ML models, datasets, and collaborating on NLP and generative AI projects.
In 7 listsDetails
Chinese-Elite
An open-source project that automatically maps relationship networks by parsing public data using LLMs and visualizes it as an interactive graph.
Desbordante
An open-source data profiler specifically focused on discovery and validation of complex patterns, such as numerical association rules, differential dependencies, denial constraints, and more.
In 4 listsDetails
dna-claude-analysis
Personal genome analysis toolkit with Python scripts analyzing raw DNA data across 17 categories (health risks, ancestry, pharmacogenomics, nutrition, psychology, and more) and generating a terminal-style single-page HTML visualization.
In 7 listsDetails
RunMat
Fast MATLAB-syntax runtime with automatic CPU/GPU execution and fused array kernels.
In 5 listsDetails
Turbostream
A terminal UI for experimenting with custom rule engines and selective LLM analysis on real-time data streams, without worrying about streaming infra or backpressure.
WFGY ProblemMap
Open source “failure atlas” of 16 recurring issues in LLM and RAG pipelines, with observable symptoms and suggested fixes for data science teams.
In 4 listsDetails
Deploybase
Track real-time GPU and LLM pricing across all cloud and inference providers.
DeepAnalyze
An agentic LLM for autonomous data science, which can autonomously complete a wide range of data science tasks without human intervention.
In 8 listsDetails
Disco
Superhuman exploratory data analysis. Finds the feature interactions and subgroup effects in tabular data that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Free for public data.
AI for Database
Chat with your database in natural language — no SQL needed. Get instant insights, build self-refreshing dashboards, and trigger automated workflows based on database changes.
In 4 listsDetails
DeepAlpha
AI crypto trading framework using LightGBM + XGBoost ensemble with 72 ML features. 70.9% walk-forward validated accuracy on out-of-sample data. Supports Bybit and Binance. MIT licensed, available on PyPI.
In 3 lists
Future AGI
Open-source platform to simulate, evaluate, trace, guardrail, route, and optimize LLM and AI agent apps in one feedback loop, so agents don't just get monitored, they self-improve. Self-hostable. Apache-2.0.
In 6 listsDetails
ipynbtopdf
Browser-based Jupyter notebook viewer and exporter that converts .ipynb notebooks to PDF, HTML, and Python without installing Python or TeX.
Literature and Media >Books
Probabilistic Machine Learning: An Introduction
by Kevin Patrick Murphy
In 2 lists
How to Lead in Data Science
Early Access
In 2 lists
Python Data Science Handbook
by Jake VanderPlas
In 2 lists
Everyday Data Science
& (cheaper PDF version)
Exploring Data Science
free eBook sampler
Exploring the Data Jungle
free eBook sampler
Math for Programmers
Early access
R in Action, Third Edition
Early Access
Data Science Bookcamp
Early access
In 2 lists
Essential Natural Language Processing
Early access
Mining Massive Datasets
free e-book comprehended by an online course
Pandas in Action
Early access
Advances in Evolutionary Algorithms
Free Download
Evolutionary Algorithms
Free Download
Advances in Genetic Programming, Vol. 3
Free Download
Genetic Algorithms and Evolutionary Computation
Free Download
Convex Optimization
Convex Optimization book by Stephen Boyd - Free Download
In 2 lists
Data Analysis with Python and PySpark
Early Access
In 2 lists
R for Data Science
This book will teach you how to do data science with R. You will learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. Exercise Solutions Authors: Garrett Grolemund and Hadley Wickham.
In 3 lists
Machine Learning Bookcamp
Early access
In 2 lists
Regression, a Friendly guide
Early Access
Deep Learning
Mathematical foundations by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
In 3 lists
Designing Cloud Data Platforms
Early Access
An Introduction to Statistical Learning with Applications in R
Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani.
In 3 lists
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
In 2 lists
Graph Algorithms for Data Science
Early Access
In 2 lists
Data Mesh in Action
Early Access
Julia for Data Analysis
Early Access
Regular Expression Puzzles and AI Coding Assistants
by David Mertz
Dive into Deep Learning
Interactive deep learning book with code implementations
In 4 listsDetails
In 2 lists
Foundations of Data Science
Free Download
Software Engineering for Data Scientists
Early Access
In 2 lists
Julia for Data Science
Early Access
JavaScript for Data Science
Free html page
Angewandte Data Science
German book about applied data science
The Math Behind Artificial Intelligence
A free FreeCodeCamp book teaching the math behind AI in plain English from an engineering point of view.
In 4 listsDetails
Executive Data Science
A high-level guide to managing data science teams and projects.
Introduction to Modern Statistics
A modern, open-access textbook on statistics with a heavy focus on data science applications.
The Art of Data Science
Focuses on the "art" of data analysis, how to ask the right questions and refine them.
In 2 lists
Literature and Media >Journals, Publications and Magazines
ICML
International Conference on Machine Learning
GECCO
The Genetic and Evolutionary Computation Conference (GECCO)
In 2 lists
Journal of Data Science
an international journal devoted to applications of statistical methods at large
In 2 lists
datatau.com/news
Like Hacker News, but for data
Medium Data Science Topic
Data Science related publications on medium
Towards Data Science Genetic Algorithm Topic
Genetic Algorithm related Publications towards Data Science
8bitconcepts
AI industry research and analysis with papers on AI pricing, enterprise adoption, and evaluation frameworks.
Literature and Media >Newsletters
AI Weekly
Curated AI intelligence briefing from industry leaders covering models, funding, policy, and applications. 3x/week since 2017, 40K+ subscribers.
DataTalks.Club
. A weekly newsletter about data-related things. Archive.
In 2 lists
The Analytics Engineering Roundup
. A newsletter about data science. Archive.
Techpresso
. A free daily newsletter covering the most impactful developments in AI, ML, and tech. Archive.
DiamantAI
. Practical AI engineering and generative AI explained simply: RAG, agents, and LLM application patterns for builders.
Bamboo Weekly
Weekly pandas exercises based on current events and real-world public data, with fully worked solutions. Issues older than two years are free, as are the first two questions + answers in current issues. Archive.
Literature and Media >Mailing lists
Working Group - Research Software Engineering in the Digital Humanities
. This is the mailing list for the Research Software Engineering in the Digital Humanities (DH-RSE) working group.
Literature and Media >Bloggers
Wes McKinney
Wes McKinney Archives.
Matthew Russell
Mining The Social Web.
Greg Reda
Greg Reda Personal Blog
Julia Evans
Recurse Center alumna
In 3 lists
Hakan Kardas
Personal Web Page
Sean J. Taylor
Personal Web Page
Drew Conway
Personal Web Page
Hilary Mason
Personal Web Page
Noah Iliinsky
Personal Blog
Matt Harrison
Personal Blog
Vamshi Ambati
AllThings Data Sciene
Prash Chan
Tech Blog on Master Data Management And Every Buzz Surrounding It
Clare Corthell
The Open Source Data Science Masters
Datawrangling
by Peter Skomoroch. MACHINE LEARNING, DATA MINING, AND MORE
Quora Data Science
Data Science Questions and Answers from experts
Siah
a PhD student at Berkeley
Louis Dorard
a technology guy with a penchant for the web and for data, big and small
Machine Learning Mastery
about helping professional programmers confidently apply machine learning algorithms to address complex problems.
In 2 lists
Daniel Forsyth
Personal Blog
Data Science Weekly
Weekly News Blog
Revolution Analytics
Data Science Blog
R Bloggers
R Bloggers
In 3 lists
The Practical Quant
Big data
Yet Another Data Blog
Yet Another Data Blog
KD Nuggets
Data Mining, Analytics, Big Data, Data, Science not a blog a portal
In 2 lists
Meta Brown
Personal Blog
Data Scientist
is building the data scientist culture.
WhatSTheBigData
is some of, all of, or much more than the above and this blog explores its impact on information technology, the business world, government agencies, and our lives.
Tevfik Kosar
Magnus Notitia
New Data Scientist
How a Social Scientist Jumps into the World of Big Data
Harvard Data Science
Thoughts on Statistical Computing and Visualization
Data Science 101
Learning To Be A Data Scientist
Data Mania Blog
The File Drawer - Chris Said's science blog
Emilio Ferrara's web page
, University of Southern California, Los Angeles, USA
In 2 lists
In 2 lists
FlowingData
Visualization and Statistics
In 3 lists
i am trask
A Machine Learning Craftsmanship Blog
Vademecum of Practical Data Science
Handbook and recipes for data-driven solutions of real-world problems
Dataconomy
A blog on the newly emerging data economy
Springboard
A blog with resources for data science learners
Analytics Vidhya
A full-fledged website about data science and analytics study material.
In 2 lists
Occam's Razor
Focused on Web Analytics.
Data School
Data science tutorials for beginners!
Colah's Blog
Blog for understanding Neural Networks!
In 2 lists
Sebastian's Blog
Blog for NLP and transfer learning!
Chris Albon's Website
Data Science and AI notes
Andrew Carr
Data Science with Esoteric programming languages
floydhub
Blog for Evolutionary Algorithms
Jingles
Review and extract key concepts from academic papers
nbshare
Data Science notebooks
Loic Tetrel
Data science blog
Chip Huyen's Blog
ML Engineering, MLOps, and the use of ML in startups
In 2 lists
Maria Khalusova
Data science blog
Aditi Rastogi
ML,DL,Data Science blog
Santiago Basulto
Data Science with Python
Akhil Soni
ML, DL and Data Science
Akhil Soni
ML, DL and Data Science
Applied AI Blogs
In-depth articles on AI, machine learning, and data science concepts with practical applications.
In 2 lists
Scaler Blogs
Educational content on software development, AI, and career growth in tech.
Mlu github
Mlu is developed amazon to help people in ml space you can learn everything from basics here with live diagrams
Jan Oliver Rüdiger
ML, DL and Data Science - with a focus on text-/data-mining
Literature and Media >Presentations
How to Share Data with a Statistician
Guide to data sharing.
In 2 lists
Literature and Media >Podcasts
Chain of Thought
AI infrastructure and developer tools, with interviews from engineering leaders and technical founders.
In 4 listsDetails
Data Engineering Podcast
Description: A show that digs deep into databases, big data pipelines, data governance, data collection, ETL, building effective data teams, and all of the other challenges faced by technology professionals working on data management.; Frequency: Once a week; Host: Tobias Macey; Runtime: 30-60…
In 5 listsDetails
Data Skeptic
Description: High level concepts in data science, and longer interview with researchers and practitioners; Host: Kyle Polich @DataSkeptic; Frequency: Once a week; Runtime: 15 - 45 mins, regularly ~25 mins
In 2 lists
In 2 lists
DataFramed
Description: Interviews with industry experts on what data science is, what problems it tries to solve and what it looks like in practice.; Host: Hugo Bowne-Anderson @hugobowne; Frequency: Once a week; Runtime: 50 - 60 mins
In 3 lists
Superdatascience
Description: Podcast that interviews various people in the data science industry.; Host: Chris Benson @chrisbenson, Daniel Whitenack @dwhitena; Frequency: Once a week; Runtime: Alternates between ~5 and ~60 mins
In 2 lists
The Analytics Engineering Podcast
How analytics engineers build and maintain data pipelines at scale.
In 2 lists
Literature and Media >YouTube Videos & Channels
Data School
Data Science Education
Neural Networks video series by Hugo Larochelle
Interesting class about neural networks available online for free by Hugo Larochelle, yet I have watched a few of those videos.
In 2 lists
AI Talks
Searchable summaries and topic index for practical AI engineering talks and conference videos.
Socialize >Facebook Accounts
Socialize >Twitter Accounts
Big Data Combine
Rapid-fire, live tryouts for data scientists seeking to monetize their models as trading strategies
Big Data Science
Big Data, Data Science, Predictive Modeling, Business Analytics, Hadoop, Decision and Operations Research.
Chris Said
Data scientist at Twitter
Clare Corthell
Dev, Design, Data Science @mattermark #hackerei
DADI Charles-Abner
#datascientist @Ekimetrics. , #machinelearning #dataviz #DynamicCharts #Hadoop #R #Python #NLP #Bitcoin #dataenthousiast
Data Science Central
Data Science Central is the industry's single resource for Big Data practitioners.
Data Science London
Data Science. Big Data. Data Hacks. Data Junkies. Data Startups. Open Data
Data Science Renee
Documenting my path from SQL Data Analyst pursuing an Engineering Master's Degree to Data Scientist
Data Science Report
Mission is to help guide & advance careers in Data Science & Analytics
Data Science Tips
Tips and Tricks for Data Scientists around the world! #datascience #bigdata
Data Vizzard
DataViz, Security, Military
DJ Patil
White House Data Chief, VP @ RelateIQ.
Drew Conway
Data nerd, hacker, student of conflict.
Erin Bartolo
Running with #BigData--enjoying a love/hate relationship with its hype. @iSchoolSU #DataScience Program Mgr.
Greg Reda
Working @ GrubHub about data and pandas
Gregory Piatetsky
KDnuggets President, Analytics/Big Data/Data Mining/Data Science expert, KDD & SIGKDD co-founder, was Chief Scientist at 2 startups, part-time philosopher.
Hadley Wickham
Chief Scientist at RStudio, and an Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University.
Hakan Kardas
Data Scientist
Hilary Mason
Data Scientist in Residence at @accel.
Jeff Hammerbacher
ReTweeting about data science
John Myles White
Scientist at Facebook and Julia developer. Author of Machine Learning for Hackers and Bandit Algorithms for Website Optimization. Tweets reflect my views only.
Juan Miguel Lavista
Principal Data Scientist @ Microsoft Data Science Team
Julia Evans
Hacker - Pandas - Data Analyze
Kenneth Cukier
The Economist's Data Editor and co-author of Big Data (https://www.big-data-book.com/).
Kevin Markham
Data science instructor, and founder of Data School
Kim Rees
Interactive data visualization and tools. Data flaneur.
Kirk Borne
DataScientist, PhD Astrophysicist, Top #BigData Influencer.
Luis Rei
PhD Student. Programming, Mobile, Web. Artificial Intelligence, Intelligent Robotics Machine Learning, Data Mining, Natural Language Processing, Data Science.
Matt Harrison
Opinions of full-stack Python guy, author, instructor, currently playing Data Scientist. Occasional fathering, husbanding, organic gardening.
Matthew Russell
Mining the Social Web.
Mert Nuhoğlu
Data Scientist at BizQualify, Developer
Monica Rogati
Data @ Jawbone. Turned data into stories & products at LinkedIn. Text mining, applied machine learning, recommender systems. Ex-gamer, ex-machine coder; namer.
Noah Iliinsky
Visualization & interaction designer. Practical cyclist. Author of vis books: https://www.oreilly.com/pub/au/4419
Paul Miller
Cloud Computing/ Big Data/ Open Data Analyst & Consultant. Writer, Speaker & Moderator. Gigaom Research Analyst.
Peter Skomoroch
Creating intelligent systems to automate tasks & improve decisions. Entrepreneur, ex-Principal Data Scientist @LinkedIn. Machine Learning, ProductRei, Networks
Prash Chan
Solution Architect @ IBM, Master Data Management, Data Quality & Data Governance Blogger. Data Science, Hadoop, Big Data & Cloud.
Quora Data Science
Quora's data science topic
R-Bloggers
Tweet blog posts from the R blogosphere, data science conferences, and (!) open jobs for data scientists.
Randy Olson
Computer scientist researching artificial intelligence. Data tinkerer. Community leader for @DataIsBeautiful. #OpenScience advocate.
Recep Erol
Data Science geek @ UALR
Ryan Orban
Data scientist, genetic origamist, hardware aficionado
Sean J. Taylor
Social Scientist. Hacker. Facebook Data Science Team. Keywords: Experiments, Causal Inference, Statistics, Machine Learning, Economics.
Silvia K. Spiva
#DataScience at Cisco
Harsh B. Gupta
Data Scientist at BBVA Compass
Spencer Nelson
Data nerd
Talha Oz
Enjoys ABM, SNA, DM, ML, NLP, HI, Python, Java. Top percentile Kaggler/data scientist
Tasos Skarlatidis
Complex Event Processing, Big Data, Artificial Intelligence and Machine Learning. Passionate about programming and open-source.
Terry Timko
InfoGov; Bigdata; Data as a Service; Data Science; Open, Social & Business Data Convergence
Tony Baer
IT analyst with Ovum covering Big Data & data management with some systems engineering thrown in.
Tony Ojeda
Data Scientist , Author , Entrepreneur. Co-founder @DataCommunityDC. Founder @DistrictDataLab. #DataScience #BigData #DataDC
Vamshi Ambati
Data Science @ PayPal. #NLP, #machinelearning; PhD, Carnegie Mellon alumni (Blog: https://allthingsds.wordpress.com )
Wes McKinney
Pandas (Python Data Analysis library).
WileyEd
Senior Manager - @Seagate Big Data Analytics @McKinsey Alum #BigData + #Analytics Evangelist #Hadoop, #Cloud, #Digital, & #R Enthusiast
WNYC Data News Team
The data news crew at @WNYC. Practicing data-driven journalism, making it visual, and showing our work.
Alexey Grigorev
Data science author
İlker Arslan
Data science author. Shares mostly about Julia programming
INEVITABLE
AI & Data Science Start-up Company based in England, UK
Jan Oliver Rüdiger
ML, DL and Data Science - with a focus on text-/data-mining
Socialize >Telegram Channels
Open Data Science
First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former.
Loss function porn
Beautiful posts on DS/ML theme with video or graphic visualization.
Machinelearning
Daily ML news.
Socialize >Slack Communities
DataTalks.Club
. A weekly newsletter about data-related things. Archive.
In 2 lists
Socialize >GitHub Groups
Socialize >Data Science Competitions
Kaggle
kaggle has built-in free jupyter notebook.; One can also connect to Google BigQuery to access big data.
In 5 listsDetails
DrivenData
Participate in data science competitions and help organizations.
In 2 lists
In 2 lists
Realtime deployment
Tutorial on Python time-series model deployment.
Fun >Datasets
ADS-B Exchange
Specific datasets for aircraft and Automatic Dependent Surveillance-Broadcast (ADS-B) sources.
Chinese Tea Dataset
Curated open dataset of 100+ Chinese teas with category, origin, caffeine level, flavor notes, oxidation, and brewing parameters. Available as JSON and CSV.
College ROI Dataset
Lifetime return-on-investment estimates for ~30K US bachelor's programs across 1,775 institutions, built from FREOPP, IPEDS, and BEA regional price data. 5 CSVs with data dictionary, CC BY 4.0, Zenodo DOI.
AI Displacement Tracker
Structured dataset tracking 92 AI-attributed workforce reduction events affecting 453,748 workers across 12 countries and 11 sectors. JSON and CSV formats. CC-BY-4.0 licensed.
Packrift Packaging Optimization Benchmark Corpus
Public packaging product dataset generated from 1,000 exact-spec SKU records, with downloadable CSV and JSON files for ecommerce fulfillment and warehouse analysis.
Pokemon Card Centering Measurements
320 measured PSA-style centering annotations (left/right and top/bottom border percentages, tilt) across 302 real eBay-listed Pokemon cards. CSV, CC BY 4.0, Zenodo DOI.
Pokemon Card Sold-Price Reference by Grade
Median sold price by grade (raw, PSA 9, PSA 10) for 486 Pokemon cards, with sample size and confidence flag per card. CSV, CC BY 4.0, Zenodo DOI.
Evidaxis Momentum Snapshots
Weekly snapshots of public development and citation activity for open-source and research-native AI systems, content-addressed and byte-reproducible from public inputs. JSON and CSV per snapshot date, CC0, DOI 10.5281/zenodo.21076011.
data.gov
The home of the U.S. Government's open data
enigma.com
Navigate the world of public data - Quickly search and analyze billions of public records published by governments, companies and organizations.
In 2 lists
aws.amazon.com/datasets
Amazon public datasets.
In 3 lists
NASDAQ:DATA
Nasdaq Data Link A premier source for financial, economic and alternative datasets.
In 2 lists
Congressional Stock Brain
Free AI-powered tool that scores U.S. congressional STOCK Act trade disclosures by significance. Machine-scored signals from 537 lawmakers's public trade filings.
In 3 lists
figshare.com
(Storage, Lookup): Data sharing and storage
In 2 lists
Hugging Face Datasets
the central index for modern NLP datasets, with versioned, streamable loaders.
In 5 listsDetails
Japan Neighborhoods
English dataset of Tokyo crime statistics across 5,078 neighborhoods × 7 years (36,222 records, 2018-2024), sourced from Tokyo Metropolitan Police open data. Includes interactive crime map, safety grading, and cost-of-living index. CC BY licensed.
In 2 lists
The Quiet-Broke Index
A 30-metro composite ranking of how much of a $400K household income gets consumed by housing, taxes, childcare, healthcare, and transport. Open methodology, free, no email gate.
In 2 lists
Crime Brasil
Open-data platform for Brazilian crime statistics. Neighborhood-level in Rio Grande do Sul (2.99M incidents across 79,024 neighborhoods, 2022–2025), municipality-level for MG and RJ, plus national PRF highway and DATASUS interpersonal-violence data. Free REST API, CSV/Parquet, daily updates, CC BY…
In 5 listsDetails
US Truck-Involved Fatal Crashes (FARS) 2018-2024
Filtered subset of NHTSA Fatality Analysis Reporting System covering 33,898 fatal crashes involving medium and heavy commercial trucks across all 50 US states, 2018-2024. Includes interactive Vision Zero Report Card comparing 19 cities, reproducible Python pipeline on GitHub, and HuggingFace…
State of Peptides 2026
Structured reference dataset of 156 peptide and peptide-adjacent compounds, each with a regulatory status bucket, category, route, half-life, molecular weight, CAS number, reference count, and PubChem/DrugBank/Wikidata IDs. CSV and JSON, no login, CC BY 4.0.
Kaggle Datasets
Extensive collection of datasets for practice in data analysis.
In 3 lists
A community-curated database of well-known people, places, and things
Large scale knowledge base originally stated by Metaweb. Later aquired by Google and used in Google Knowledge Graph.
In 3 lists
In 2 lists
World Bank Data
Free and open access to global development data by The World Bank.
In 3 lists
Open Data Philly
Connecting people with data for Philadelphia
grouplens.org
Sample movie (with ratings), book and wiki datasets
UC Irvine Machine Learning Repository
contains data sets good for machine learning
research-quality data sets
by Hilary Mason
National Centers for Environmental Information
(Lookup): Weather, climate, coasts, oceans, and geophysics etc
In 2 lists
ClimateData.us
(related: U.S. Climate Resilience Toolkit)
r/datasets
Datasets for Data Mining, Analytics and Knowledge Discovery.
In 3 lists
MapLight
provides a variety of data free of charge for uses that are freely available to the general public. Click on a data set below to learn more
GHDx
Institute for Health Metrics and Evaluation - a catalog of health and demographic datasets from around the world and including IHME results
Open Data Sources
Collection of various open data sources.
In 2 lists
undata
Data from the UN
In 3 lists
The GDELT Project
The GDELT Project monitors the world's broadcast, print, and web news from nearly every corner of every country in over 100 languages and identifies the people, locations, organizations, themes, sources, emotions, counts, quotes, images and events driving our global society every second of every…
In 3 lists
StackExchange Data Explorer
an open source tool for running arbitrary queries against public data from the Stack Exchange network.
Public Git Archive
6 TB of Git repositories from GitHub.
In 2 lists
Google Dataset Search (beta)
Dataset Search is a search engine for datasets. Using a simple keyword search, users can discover datasets hosted in thousands of repositories across the Web.
In 6 listsDetails
250k+ Job Postings
An expanding dataset of historical job postings from Luxembourg from 2020 to today. Free with 250k+ job postings hosted on AWS Data Exchange.
FinancialData.Net
Financial datasets (stock market data, financial statements, sustainability data, and more).
In 2 lists
HDD Price Index
Daily open dataset of the cheapest new internal 3.5" SATA hard-drive price per terabyte (USD/TB) by capacity tier on Amazon US, with a historical time series. CSV, JSON and JSONL, no login, CC BY 4.0.
BDE Score
AI-powered multi-market stock analysis with transparent BDE scoring across 73 stocks (US/HK/A-share). EU AI Act Art.50 compliant. MIT license.
In 4 listsDetails
notesjor corpus-collection
Free corpora (over 6 billion tokens) mostly German (both historically and in contemporary German).
CLARIN-Repository
CLARIN is a European repository for scientific datasets.
GBIF
Global Biodiversity Information Facility: 2.4B+ species occurrence records. Free, open API for ecological modeling and ML research.
In 3 lists
FAOSTAT
UN FAO statistics on food production, trade, land use, and emissions for 245+ countries. Free API and bulk download.
Movebank
Free platform archiving 6B+ animal movement records from GPS and satellite telemetry. Open REST API, useful for spatiotemporal modeling and trajectory ML.
Encyclopedia of Life
Open structured data on 1.9M+ species, including traits, classification, and media. Free API and bulk downloads for biodiversity and species-classification tasks.
FirstData
The world's most comprehensive authoritative data source knowledge base. 210+ curated sources from governments, international organizations, and research institutions. MCP integration for AI agents. MIT licensed.
In 2 lists
latamdata-py
Python package for one-line access to 38 open research datasets from Latin America (health, neuroscience, mental health, economics). pip install latamdata-py.
ZipCheckup
Free ZIP-level environmental safety data for 42,000+ US ZIP codes: water quality, air quality, PFAS contamination, radon, lead, flood risk, and 11 more verticals. Public REST API, npm/PyPI packages, CC BY 4.0.
In 3 lists
Helium
Real-time news corpus with structured bias features across 15+ dimensions (3.2M+ articles, 5,000+ sources), live financial market data (stocks, ETFs, crypto) with AI-generated analysis, ML options pricing with probability metrics and full Greeks, historical options chain data for quantitative…
In 3 lists
Verified Supplement Evidence
Evidence-graded dietary-supplement dataset covering dosing, bioavailability by form, drug-nutrient interactions, NHANES deficiency prevalence, FDA FAERS adverse-event signals, and cost-per-effective-dose, with every clinical claim citing a PubMed PMID. CC BY 4.0, DOI 10.57967/hf/9356.
WhatFontIs-Bench
Synthetic benchmark for font family identification with 11,995 images of words set in 600 known fonts, annotated with word and per-letter boxes.
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