How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Skorch is a deep learning workflow manager and tensor-based model interface. It provides a consistent API for training and predicting with neural networks within standard machine learning workflows, acting as a hyperparameter optimizer for finding optimal network configurations. The library specializes in wrapping PyTorch neural networks in a scikit-learn compatible interface. This allows tensor-based models to be used within traditional machine learning pipelines and grid search tools, including the mapping of parameter grids to model configurations. The framework covers training lifecycle
The main features of pytorchlightning/lightning-flash are: Developer Tools, Training and Experimentation.
Projects with overlapping indexed features include: catalyst-team/catalyst — Accelerated deep learning R&D. ecs-vlc/torchbearer — torchbearer: A model fitting library for PyTorch. asappresearch/flambe. backprop-ai/backprop — Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. dnouri/skorch — Skorch is a deep learning workflow manager and tensor-based model interface. It provides a consistent API for training… facebook/ax — Adaptive Experimentation Platform.
