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gan-tensorflow

This's a re-implementation of generative adversarial networks using tensorflow.

gnnpapers

Must-read papers on graph neural networks (GNN)

gnn_review

GNN综述阅读报告

graphneuralnetwork

《深入浅出图神经网络：GNN原理解析》配套代码

hands-on-ml-zh

:book: [译] Sklearn 与 TensorFlow 机器学习实用指南【版权问题，网站已下线！！】

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

itktubetk

An open-source toolkit, led by Kitware, Inc., for the segmentation, registration, and analysis of tubes and surfaces in images.

it_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）

keras

Deep Learning for humans

keras-gan

Keras implementations of Generative Adversarial Networks.

kubeflow

Machine Learning Toolkit for Kubernetes

luna16_multi_size_3dcnn

An implement of paper "Multi-level Contextual 3D CNNs for False Positive Reduction in Pulmonary Nodule Detection"

machine-learning-for-photovoltaic-material-property-prediction

Multi-layer perceptron model for photo-voltaic material properties prediction.

machine_learning_perovskite_tutorial

Tutorial for performing machine learning to predict band gaps from the K computer double perovskite dataset

makeyourownneuralnetwork

Code for the Make Your Own Neural Network book

ml-based-on-tensorflow

基于Tensorflow的深度学习

mmdetection

Open MMLab Detection Toolbox

models

Models and examples built with TensorFlow

moleculargnn_3dstructure

Graph neural network (GNN) for molecular property prediction (3D structure)

moleculargnn_smiles

The code of a graph neural network (GNN) for molecules, which is based on learning representations of r-radius subgraphs (i.e., fingerprints) in molecules.

nips17-rexgen

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network (NIPS 2017)

non-supervision-test

无人监考团队的存储库

oreilly-learning-tensorflow

organic

Code repo for optimizing distributions of molecules.

pro-gnn

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

python-machine-learning-second-edition

Python Machine Learning - Second Edition, published by Packt

pythondatamining

:notebook_with_decorative_cover: 在学院的书架上发现了一本不带脑子就能看懂的书《Python数据挖掘与实战》