Awesome Blogs
Section: Awesome AutoDL Libraies
Entry
Appears in 5 awesome lists
Deep learning training platform with integrated support for distributed training, hyperparameter tuning, smart GPU scheduling, experiment tracking, and a model registry.
Section: Awesome AutoDL Libraies
Section: Tools · Deep learning training platform with integrated support for distributed training, hyperparameter tuning, smart GPU scheduling, experiment tracking, and a model registry.
Section: AutoML · scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.
Section: Python · Scalable deep learning training platform, including integrated support for distributed training, hyperparameter tuning, experiment tracking, and model management.
Section: Model Training and Orchestration · Deep learning training platform with integrated support for distributed training, hyperparameter tuning, and model management (supports Tensorflow and Pytorch).
Visualizer for deep learning and machine learning models (no Python code, but visualizes models from most Python Deep Learning frameworks).
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).
The agent simulation, evaluation, and observability platform helping product teams ship their AI applications with the quality and speed needed for real-world use.
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.
Community-friendly platform supporting data scientists in creating and sharing machine learning models. Neptune facilitates teamwork, infrastructure management, models comparison and reproducibility.
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.