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Visualizer for neural network, deep learning and machine learning models

:zap: A Fast, Extensible Progress Bar for Python and CLI

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Open standard for machine learning interoperability

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

AutoML library for deep learning

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 Reinforcement Learning for Keras.

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

AI Infra / AI Orchestration / AI Control Plane

Deep neural network to extract intelligent information from invoice documents.

Graph Neural Networks with Keras and Tensorflow 2.

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Python AutoML for Trading Systems and Sports Betting

Hyperparameter Experiments with TensorFlow and Keras

Keras community contributions

Distributed Deep learning with Keras & Spark

MLBox is a powerful Automated Machine Learning python library.

Pretrained model hub for Keras 3.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

QKeras: a quantization deep learning library for Tensorflow Keras

Data Preparation for Satellite Machine Learning

tutorials made for biologists to learn deep learning