Tensors and Dynamic neural networks in Python with strong GPU acceleration
Repository Index
47,133 repositories indexed
1–24 of 43 · Most stars
Deep Learning for humans
We write your reusable computer vision tools. 💜
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
100-Days-Of-ML-Code中文版
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Open standard for machine learning interoperability
Open Machine Learning Compiler Framework
机器学习相关教程
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
TensorFlow-based neural network library
Deep learning library featuring a higher-level API for TensorFlow.
AutoML library for deep learning
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Largest list of models for Core ML (for iOS 11+)
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Deep Reinforcement Learning for Keras.
:earth_americas: Simple and ready-to-use tutorials for TensorFlow