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.

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

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Build your neural network easy and fast, 莫烦Python中文教学

A scikit-learn compatible neural network library that wraps PyTorch

温州大学《机器学习》课程资料（代码、课件等）

Python implementation of CMA-ES

Investigating PINNs

Implementation of simple autoencoders networks with Keras

吴恩达深度学习课程课后编程作业

MSc group project: Reproduction of 'Multi-Task Learning using Uncertainty to Weigh Losses for Scene Geometry and Semantics'; A. Kendall, Y. Gal, R. Cipolla

基于PyTorch使用迁移学习完成项目

This is Keras code from "Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders".