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TensorFlow is an open-source machine learning framework for building and deploying ML models.
PyTorch is a Python library for tensor computation and deep learning with GPU acceleration.
Real-time infrastructure monitoring with AI-powered insights and zero configuration.
TensorFlow Model Garden with SOTA implementations
X's recommendation algorithm source code
Curated list of machine learning frameworks, libraries, and software
Python machine learning library for data analysis and statistics
Keras 3 is a multi-backend deep learning framework for building and training models with support for JAX, TensorFlow, PyTorch, and OpenVINO.
Learn to build production-grade ML applications with code and best practices
Beginner-friendly AI curriculum with 12 weeks, 24 lessons, covering TensorFlow, PyTorch, and AI ethics.
AI learning repository with tutorials and implementations for machine learning, deep learning, and data analysis
DeepSpeed optimizes deep learning training and inference with distributed computing techniques.
Ray is a unified framework for scaling AI and Python applications with distributed computing and ML libraries.
Colossal-AI optimizes large AI model training and inference with distributed computing and GPU acceleration.
JAX is a high-performance numerical computing library for Python, enabling transformations like differentiation and JIT compilation for GPUs/TPUs.
Caffe is a fast deep learning framework for vision and machine learning tasks.
tinygrad is a lightweight deep learning framework combining PyTorch-like ergonomics with compiler visibility and JIT execution.
PyTorch Lightning simplifies deep learning training and deployment at scale.
Hands-on Machine Learning with Python, Scikit-Learn, Keras, and TensorFlow 2.
Data science Python notebooks covering deep learning, machine learning, big data, and more.
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