:zap: A Fast, Extensible Progress Bar for Python and CLI
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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.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
100-Days-Of-ML-Code中文版
Open standard for machine learning interoperability
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
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.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
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
Hyperparameter Experiments with TensorFlow and Keras
Distributed Deep learning with Keras & Spark
MLBox is a powerful Automated Machine Learning python library.
Pretrained model hub for Keras 3.
kapre: Keras Audio Preprocessors
PyTorch to Keras model convertor
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
Trading Environment(OpenAI Gym) + DDQN (Keras-RL)