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Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
An opinionated list of awesome Python frameworks, libraries, software and resources.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
🦜🔗 The platform for reliable agents.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
FastAPI framework, high performance, easy to learn, fast to code, ready for production
The Web framework for perfectionists with deadlines.
Models and examples built with TensorFlow
A curated list of awesome Machine Learning frameworks, libraries and software.
Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to clo…
scikit-learn: machine learning in Python
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Financial data platform for analysts, quants and AI agents.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Streamlit — A faster way to build and share data apps.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
A toolkit for developing and comparing reinforcement learning algorithms.