https://github.com/silenceoverflow/cs-learning-resources
Learning Resources for Those New to Computer Science
https://github.com/silenceoverflow/cs-learning-resources
algorithm computer-science machine-learning mooc programming
Last synced: about 1 month ago
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Learning Resources for Those New to Computer Science
- Host: GitHub
- URL: https://github.com/silenceoverflow/cs-learning-resources
- Owner: SilenceOverflow
- License: mit
- Created: 2017-04-20T13:45:06.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2018-03-10T20:28:37.000Z (about 7 years ago)
- Last Synced: 2025-04-12T20:06:55.275Z (about 1 month ago)
- Topics: algorithm, computer-science, machine-learning, mooc, programming
- Homepage: https://youjiexia.github.io/CS-Learning-Resources/
- Size: 7.81 KB
- Stars: 20
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://youjiexia.github.io/2017/04/19/Learning-Resources-for-Computer-Science/) or [Link2](https://youjiexia.github.io/CS-Learning-Resources/).
>
> **Updating**!
>
> Last Update: Mar. 10, 2018.
* content
{:toc}
## Open Courses and Online Resources
### Algorithms
- [Algorithms](http://algs4.cs.princeton.edu/), (@Princeton) or [Algorithms, Part I](https://www.coursera.org/learn/algorithms-part1) / [Part II](https://www.coursera.org/learn/algorithms-part2), (@Coursera)
- [VisuAlgo.Net](https://visualgo.net/en): visualising data structures and algorithms through animation
- [Algorithms](https://www.khanacademy.org/computing/computer-science/algorithms), (@Khan Academy)
### Autonomous Driving
- [Visual Perception for Autonomous Driving](http://www.cs.toronto.edu/~urtasun/courses/CSC2541/CSC2541_Winter16.html), (**CSC2541**@Toronto)
- [Deep Learning for Self-Driving Cars](http://selfdrivingcars.mit.edu), (**6.S094**@MIT/SUTD)
### Computer Vision
- [Computer Vision](http://www.andrew.cmu.edu/course/16-720/), (**16-720**@CMU, Prof. Martial Hebert)
- [Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu), [[网易云课堂](http://study.163.com/course/courseMain.htm?courseId=1003223001)], (**CS231n**@Stanford, Prof. Fei-Fei Li)
### Data Science
- [Pratical Data Science](http://www.datasciencecourse.org/), (**15-388/688**@CMU)
### Deep Learning
- [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning), (@Coursera, Prof. Andrew Ng)
- [Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu), [[网易云课堂](http://study.163.com/course/courseMain.htm?courseId=1003223001)], (**CS231n**@Stanford, Prof. Fei-Fei Li)
- [Introduction to Deep Learning](http://introtodeeplearning.com/index.html), (**6.S191**@MIT)
- [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks), (@Coursera, Prof. Geoffrey Hinton)
- [Practical Deep Learning For Coders, Part 1](http://course.fast.ai/index.html), (@USF)
- [Deep Reinforcement Learning, Spring 2017](http://rll.berkeley.edu/deeprlcourse/), (**CS294**@UC Berkeley)
- [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/index.html), a free online book
### Introduction to Computer Science
- [Introduction to Computer Systems](https://www.cs.cmu.edu/~213/index.html), (**15-213**@CMU)
- [Fundamentals of Computing](https://www.coursera.org/specializations/computer-fundamentals), (@Coursera, @Rice)
- [Intensive Introduction to Computer Science Open Learning Course](https://cs50.harvard.edu/weeks), (**CS50**@Harvard)
- Introduction to Computer Science and Programming Using Python, [[@edX](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-10#!)], [[**6.0001**@MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/index.htm)], [[@网易公开课](http://open.163.com/special/opencourse/bianchengdaolun.html)]
### Machine Learning
- [Complete Notes of Stanford's Machine Learning Course](http://www.holehouse.org/mlclass/index.html), (@HoleHouse)
- [Machine Learning](https://www.coursera.org/learn/machine-learning), (@Coursera, Prof. Andrew Ng)
- [Machine Learning for Data Analysis](https://www.coursera.org/learn/machine-learning-data-analysis), (@Coursera, @Wesleyan)
- [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks), (@Coursera, Prof. Geoffrey Hinton)
- [Machine Learning (2017,Fall)](http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17.html), (@NTU, Dr. Hung-yi Lee/李宏毅博士)
- [机器学习](https://book.douban.com/subject/26708119/), (@Prof. Zhihua Zhou/周志华教授)
- [机器学习的发展历程及启示](http://mt.sohu.com/20170326/n484898474.shtml), (@Prof. Zhihua Zhang/张志华教授)
- [统计学习方法](https://book.douban.com/subject/10590856/), (@Dr. Hang Li/李航博士)
### PyTorch
- [PyTorch Tutorials](https://github.com/chenyuntc/pytorch-book)
- [PyTorch Guide - 知乎](https://zhuanlan.zhihu.com/p/26670032)
- [PyTorch中文文档](http://pytorch-cn.readthedocs.io/zh/latest/)
- [PyTorch入门教程](https://morvanzhou.github.io/tutorials/machine-learning/torch/)
### TensorFlow
- [Tensorflow for Deep Learning Research](http://web.stanford.edu/class/cs20si/index.html), (**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](https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650726048&idx=1&sn=492ccde81a2ca2a344f995c5f92a3107&chksm=871b1adeb06c93c87b81f9c6a9e6e041e01a2885949d16e8a7e758a26a0237421b59257de7a4&mpshare=1&scene=1&srcid=04302CkKlQxEW1SKu1lvTtcc&key=c9ae00cb2e00c8e8d2617194d0069ed95f2478e55d55de759e8fa0716800107b81366e564ed7e28a157342e083b7d7ec4d151376fe0db3c19eef556c9d15945be8ea49770b08cbb4f9d3a6799a02fcb6&ascene=0&uin=MTA0MDA5MTMwMw%3D%3D&devicetype=iMac+MacBookPro11%2C4+OSX+OSX+10.11.6+build(15G1421)&version=12020110&nettype=WIFI&fontScale=100&pass_ticket=Z6eFtF9%2B8uZcT8c1EnvoXMh%2BVdS7%2B7YjXXJ68IGu2xLz35jNKc0MKihKUY%2FbB4Dk)
- [TensorFlow入门教程](https://morvanzhou.github.io/tutorials/machine-learning/tensorflow/)
## Programming Languages
### General Guide
- [Beginner’s Resources to Learn Programming Languages](https://www.vodien.com/blog/education/beginners-resources-to-learn-programming-languages.php), (Recommended by Adam)
### Java
- [IntelliJ IDEA](https://www.jetbrains.com/idea/), (IDE @JetBrains)
- [Learn Java](https://www.codecademy.com/en/courses/learn-java), (@Codecademy)
### JavaScript
- [Learn JavaScript](https://www.codecademy.com/learn/learn-javascript), (@Codecademy)
- [JavaScript教程](http://www.liaoxuefeng.com/wiki/001434446689867b27157e896e74d51a89c25cc8b43bdb3000), (@廖雪峰的官方网站)
### Python
- [ANACONDA](https://www.continuum.io/downloads/), (With over 720 popular packages easily installed popular, like **Jupyter Notebook**, **numpy**, **scikit-learn**, **scipy**, **matplotlib**)
- [PyCharm](https://www.jetbrains.com/pycharm/), (IDE @JetBrains)
- [Python](https://www.codecademy.com/learn/python), (@Codecademy)
- [Video: Official Guide to Python](http://v.qq.com/vplus/8b0c0b53f338d17267d5bd9617482a49/foldervideos/2dq0001010wz5wm), (@JetBrains)
- [Python教程](http://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000), (@廖雪峰的官方网站)
#### Jupyter Notebook
- Getting started with the Jupyter notebook, [[Part 1](https://www.packtpub.com/books/content/getting-started-jupyter-notebook-part-1)/[中文版](http://codingpy.com/article/getting-started-with-jupyter-notebook-part-1/)], [[Part 2](https://www.packtpub.com/books/content/getting-started-jupyter-notebook-part-2)/[中文版](http://codingpy.com/article/getting-started-with-jupyter-notebook-part-2/)]
#### Matplotlib
- [An Introduction to Scientific Python – Matplotlib](http://www.datadependence.com/2016/04/scientific-python-matplotlib/), [[中文版](http://codingpy.com/article/a-quick-intro-to-matplotlib/)]
#### Numpy
- [Python Numpy Tutorial](http://cs231n.github.io/python-numpy-tutorial/)
- [An Introduction to Scientific Python – NumPy](http://www.datadependence.com/2016/05/scientific-python-numpy/), [[中文版](http://codingpy.com/article/an-introduction-to-numpy/)]
### MATLAB
- [MATLAB SKY](http://www.kui4.com/freev.html), (Easy for Beginners)
## Platforms & Tools
### Git / Github
- [GitHub：GitHub官方入门教学视频](http://www.stuq.org/course/969/study)
- [Git教程](http://www.liaoxuefeng.com/wiki/0013739516305929606dd18361248578c67b8067c8c017b000), (@廖雪峰的官方网站)
### Linux
- [鸟哥的Linux私房菜](http://cn.linux.vbird.org/linux_basic/linux_basic.php)
### Markdown
- [StackEdit - An Online Markdown Editor](https://stackedit.io/)
## Websites
### Competitions & Datasets
- [AI Challenger/全球AI挑战赛](challenger.ai)
- [DataCastle](http://www.pkbigdata.com)
- [ImageNet](http://image-net.org)
- [Kaggle](https://www.kaggle.com)
### Tutorial Sites
- [Coursera](https://www.coursera.org)
- [IMOOC / 慕课网](http://www.imooc.com)
- [Khan Academy](https://www.khanacademy.org)
- [RUNOOB / 菜鸟教程](http://www.runoob.com)
- [Udacity](https://cn.udacity.com)
- [W3Cschool](http://www.w3cschool.cn)
- [廖雪峰的官方网站](http://www.liaoxuefeng.com), (Tutorials for [Java](http://www.liaoxuefeng.com/webpage/java) / [JavaScript](http://www.liaoxuefeng.com/wiki/001434446689867b27157e896e74d51a89c25cc8b43bdb3000) / [Python](http://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000) / [Git](http://www.liaoxuefeng.com/wiki/0013739516305929606dd18361248578c67b8067c8c017b000))
### Programming Sites
- [Codecademy](https://www.codecademy.com)
- [LeetCode Online Judge](https://leetcode.com)
- [实验楼](https://www.shiyanlou.com)
----
> Author: [@YoujieXia](http://youjiexia.github.io/) More Articles：[PersonalSite/个人网站](http://youjiexia.github.io/) `|` [CSDN](http://blog.csdn.net/cxsydjn) `|` [简书](http://www.jianshu.com/users/c357c55f62dc/timeline)