Machine Learning & Deep Learning Packages
Machine-learning and deep-learning frameworks and model libraries for training, fine-tuning, and serving models (PyTorch, scikit-learn, Transformers).
Packages in Machine Learning & Deep Learning
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Transformers
State-of-the-art pretrained models for text, vision, audio, and multimodal inference and training.
Gradio
Build and share machine learning web apps and demos in pure Python.
PySpark
Python API for Apache Spark, the unified engine for large-scale distributed data processing
PyTorch Lightning
A deep learning framework that organizes PyTorch training code and automates multi-GPU, mixed-precision, and distributed training.
MLflow
Open source AI engineering platform for tracking, evaluating, and shipping ML models, LLMs, and agents to production.
ModelScope
Alibaba's open model-hub library for NLP, CV, speech, and multi-modal AI models.
PyTorch Lightning
The deep learning framework that separates PyTorch research code from engineering boilerplate, scaling from CPU to multi-node GPU clusters without code changes.
dspy
DSPy replaces brittle prompt engineering with compositional Python code, letting optimizers tune your language model pipeline's prompts and weights automatically.
fastai
A high-level deep learning framework that layers state-of-the-art training APIs on top of PyTorch.
DeepEval
A Pytest-like open-source framework for unit-testing and evaluating LLM applications with research-backed metrics.
BasicSR
An open-source PyTorch toolbox for image and video restoration, covering super-resolution, denoising, deblurring, and face restoration.
GEPA
Optimize prompts, code, and agents with LLM reflection and evolutionary search
BrowserGym Core
Gymnasium environment for building and evaluating LLM-driven web agents in a real Chromium browser.
