💫 Industrial-strength Natural Language Processing (NLP) in Python
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Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Best Practices on Recommendation Systems
Open standard for machine learning interoperability
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
🐍 Geometric Computer Vision Library for Spatial AI
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
TensorFlow-based neural network library
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Build Graph Nets in Tensorflow
A PyTorch Library for Accelerating 3D Deep Learning Research
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Interpretability and explainability of data and machine learning models
Hyperparameter Experiments with TensorFlow and Keras
A micro neural network multilayer perceptron for MicroPython (used on ESP32 and Pycom modules)