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⚠ Colab provides a temporary environment: anything you do will be deleted after a while, so make sure you download any data you care about.

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

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML.

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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…

Netron is a viewer for neural network, deep learning and machine learning models.

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

tqdm derives from the Arabic word taqaddum (تقدّم) which can mean "progress," and is an abbreviation for "I love you so much" in Spanish (te quiero demasiado).

机器学习相关教程

Magika is a novel AI-powered file type detection tool that relies on the recent advance of deep learning to provide accurate detection.

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

This project is for the second edition, which is now outdated (it came out in 2019).

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.

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

The neural network is built in three iterations. Starting with a Hello World version, followed by the main neural network layers, and ending by training it to generalize.

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes.

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.

100-Days-Of-ML-Code中文版

We recommend running these notebooks on Colab, which provides a hosted runtime with all the dependencies you will need. You can also, run these notebooks locally, either by setting up your own Jupyter environment, or using Colab's instructions for running locally.

Essential Cheat Sheets for deep learning and machine learning researchers

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

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library.

This project is about explaining what machine learning classifiers (or models) are doing.

一款入门级的人脸、视频、文字检测以及识别的项目.