Popular GitHub Repositories for Keras Forecasting

Visualizer for neural network, deep learning and machine learning models

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.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

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

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

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

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

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

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

一款入门级的人脸、视频、文字检测以及识别的项目.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Techniques for deep learning with satellite & aerial imagery

AutoML library for deep learning

Fast and Accurate ML in 3 Lines of Code

Keras implementations of Generative Adversarial Networks.

A unified framework for machine learning with time series

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)