Keras GitHub Repositories

Visualizer for neural network, deep learning and machine learning models

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

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

🏆 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

100-Days-Of-ML-Code中文版

Open standard for machine learning interoperability

A neural network that transforms a design mock-up into a static website.

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

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

Keras implementations of Generative Adversarial Networks.

A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统

A course in reinforcement learning in the wild

股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、大模型、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易

Setup and customize deep learning environment in seconds.

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.

T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

Deep Reinforcement Learning for Keras.

Tools to Design or Visualize Architecture of Neural Network

Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js

Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.

A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

Run Keras models in the browser, with GPU support using WebGL

unet for image segmentation

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.