This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

See https://meta.wikimedia.org/wiki/Research:Modeling_Talk_Page_Abuse

pandas cheetsheet

Build, train & debug, and deploy & monitor with Amazon SageMaker

IPython magics for generating figures with TikZ

Volumetric Correspondence Networks for Optical Flow, NeurIPS 2019.

Python机器学习，机器学习入门首选。

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

Data, tools, and documentation of the Fusion 360 Gallery Dataset

⚛ 10 week Practical Course on Quantum Information Science and Quantum Computing - with Qiskit and IBMQX

Samples for Azure Synapse Analytics

julia version of 100 numpy exercises

Adaptive Neural Trees

python implementations of Analyzing Neural Time Series Textbook

Predicts real-time bitcoin price using twitter and reddit sentiment, and sends out notifications via SMS.

A collection of non-residential buildings for performance analysis and algorithm benchmarking

Resources for a 3.5 hour workshop on machine learning using the MLJ toolbox

PyTorch library for "Neural Painters: A learned differentiable constraint for generating brushstroke paintings"

Python implementation of TextRank for phrase extraction and summarization of text documents