1.d2l-ai / d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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14 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Open standard for machine learning interoperability
:zap: A Fast, Extensible Progress Bar for Python and CLI
Graph Neural Networks with Keras and Tensorflow 2.
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.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
一款入门级的人脸、视频、文字检测以及识别的项目.
AutoML library for deep learning
Pretrained model hub for Keras 3.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Deep neural network to extract intelligent information from invoice documents.
PyTorch to Keras model convertor
QKeras: a quantization deep learning library for Tensorflow Keras
Neural networks toolbox focused on medical image analysis