Popular GitHub Repositories for Auto Keras

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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.

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

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.

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

Keras implementations of Generative Adversarial Networks.

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

Detect file content types with deep learning