Awesome Data Analysis
Section: Resources · AI native data science notebook platform compatible with Jupyter, featuring real-time collaboration, environment management, and integrations.
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Appears in 6 awesome lists
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps.
Section: Resources · AI native data science notebook platform compatible with Jupyter, featuring real-time collaboration, environment management, and integrations.
Section: Tools · Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps.
Section: Data Exploration · Drop-in replacement for Jupyter and an AI-native workspace for modern data teams.
Section: 13. Developer Tools & Integrations · Drop-in replacement for Jupyter with AI-first design, sleek UI, and native data integrations. Use Python, R, and SQL locally, then scale to Deepnote cloud for collaboration and deployable data apps. Apache 2.0 licensed.
Section: Data Science Notebook · Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps.
Section: Deployment · Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps.
Transpile trained ML models into other languages. sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others. mlflow - Manage the machine learning lifecycle, including experimentation, reproducibility and deployment. skll - Command-line utilities to make it easier…
Test your prompts, models, RAGs. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality. LLM evals for OpenAI/Azure GPT, Anthropic Claude, VertexAI Gemini, Ollama, Local & private models like Mistral/Mixtral/Llama with CI/CD
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).
| Python | - A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.
AI-native database built for LLM applications with incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text. Powers RAGFlow's document engine. Apache 2.0 licensed.
Praison AI is a low-code, centralized framework leveraging AutoGen and CrewAI to simplify creating and orchestrating multi-agent systems for LLM applications, emphasizing customization and ease of human-agent interaction github | demo | website