Learning Resources for Computer Science (Updating)

Here is a resource summary for learning computer science. All the materials are divided into three categories and arranged in alphabetical order.

Also, this is a To-Do list for me. I hope this could be a beginner's guide to some specific fields in or related to computer science, such as machine learning, computer vision, and SLAM, etc.

You may refer to a webpage version here Link1 or Link2.

Updating!

Last Update: Mar. 10, 2018.

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Open Courses and Online Resources

Algorithms

• Algorithms, (@Princeton) or Algorithms, Part I / Part II, (@Coursera)
• VisuAlgo.Net: visualising data structures and algorithms through animation
• Algorithms, (@Khan Academy)

Autonomous Driving

• Visual Perception for Autonomous Driving, (CSC2541@Toronto)
• Deep Learning for Self-Driving Cars, (6.S094@MIT/SUTD)

Computer Vision

• Computer Vision, (16-720@CMU, Prof. Martial Hebert)
• Convolutional Neural Networks for Visual Recognition, [网易云课堂], (CS231n@Stanford, Prof. Fei-Fei Li)

Data Science

• Pratical Data Science, (15-388/688@CMU)

Deep Learning

• Deep Learning Specialization, (@Coursera, Prof. Andrew Ng)
• Convolutional Neural Networks for Visual Recognition, [网易云课堂], (CS231n@Stanford, Prof. Fei-Fei Li)
• Introduction to Deep Learning, (6.S191@MIT)
• Neural Networks for Machine Learning, (@Coursera, Prof. Geoffrey Hinton)
• Practical Deep Learning For Coders, Part 1, (@USF)
• Deep Reinforcement Learning, Spring 2017, (CS294@UC Berkeley)
• Neural Networks and Deep Learning, a free online book

Introduction to Computer Science

• Introduction to Computer Systems, (15-213@CMU)
• Fundamentals of Computing, (@Coursera, @Rice)
• Intensive Introduction to Computer Science Open Learning Course, (CS50@Harvard)
• Introduction to Computer Science and Programming Using Python, [@edX], [6.0001@MIT], [@网易公开课]

Machine Learning

• Complete Notes of Stanford's Machine Learning Course, (@HoleHouse)
• Machine Learning, (@Coursera, Prof. Andrew Ng)
• Machine Learning for Data Analysis, (@Coursera, @Wesleyan)
• Neural Networks for Machine Learning, (@Coursera, Prof. Geoffrey Hinton)
• Machine Learning (2017,Fall), (@NTU, Dr. Hung-yi Lee/李宏毅博士)
• 机器学习, (@Prof. Zhihua Zhou/周志华教授)
• 机器学习的发展历程及启示, (@Prof. Zhihua Zhang/张志华教授)
• 统计学习方法, (@Dr. Hang Li/李航博士)

PyTorch

• PyTorch Tutorials
• PyTorch Guide - 知乎
• PyTorch中文文档
• PyTorch入门教程

TensorFlow

• Tensorflow for Deep Learning Research, (CS 20SI@Standford)
• TensorFlow初学者指南：如何为机器学习项目创建合适的文件架构
• TensorFlow入门教程

Programming Languages

General Guide

• Beginner’s Resources to Learn Programming Languages, (Recommended by Adam)

Java

• IntelliJ IDEA, (IDE @JetBrains)
• Learn Java, (@Codecademy)

JavaScript

• Learn JavaScript, (@Codecademy)
• JavaScript教程, (@廖雪峰的官方网站)

Python

• ANACONDA, (With over 720 popular packages easily installed popular, like Jupyter Notebook, numpy, scikit-learn, scipy, matplotlib)
• PyCharm, (IDE @JetBrains)
• Python, (@Codecademy)
• Video: Official Guide to Python, (@JetBrains)
• Python教程, (@廖雪峰的官方网站)

Jupyter Notebook

• Getting started with the Jupyter notebook, [Part 1/中文版], [Part 2/中文版]

Matplotlib

• An Introduction to Scientific Python – Matplotlib, [中文版]

Numpy

• Python Numpy Tutorial
• An Introduction to Scientific Python – NumPy, [中文版]

MATLAB

• MATLAB SKY, (Easy for Beginners)

Platforms & Tools

Git / Github

• GitHub：GitHub官方入门教学视频
• Git教程, (@廖雪峰的官方网站)

Linux

• 鸟哥的Linux私房菜

Markdown

• StackEdit - An Online Markdown Editor

Websites

Competitions & Datasets

• AI Challenger/全球AI挑战赛
• DataCastle
• ImageNet
• Kaggle

Tutorial Sites

• Coursera
• IMOOC / 慕课网
• Khan Academy
• RUNOOB / 菜鸟教程
• Udacity
• W3Cschool
• 廖雪峰的官方网站, (Tutorials for Java / JavaScript / Python / Git)

Programming Sites

• Codecademy
• LeetCode Online Judge
• 实验楼

Author: @YoujieXia More Articles：PersonalSite/个人网站 | CSDN | 简书