做者:chen_h
微信号 & QQ:862251340
微信公众号:coderpai
博客地址:http://www.jianshu.com/p/5084...python
如今网上有不少的机器学习材料,让人一会儿看不过来。因此,我一直想写这篇文章,来帮助你们整理一些简单的资源。git
我推荐的资源包括但不限于书籍,课程,讲座,博客和一些 Jupyter 笔记。在我看来,多种类型的文件学习对本身是由帮助的。但一次性看的太多可能会让你很是不适应。为了解决这个不适应,我建议天天学习几小时是一个比较好的方案。好比:github
接下来,让咱们看看这个简短的学习材料列表:算法
1.1 Machine Learning with Python,来自 CognitiveClass.ai编程
1.2 Intro to Machine Learning,来自 Udacity微信
1.3 Machine Learning,来自 Udacity机器学习
1.4 Principles of Machine Learning,来自 EDXide
1.5 Machine Learning Crash Course,来自 Berkeley学习
2.1 Python for Data Analysis – Wes Mckineyui
2.2 Python Machine Learning – Sebastian Raschka
2.3 Introduction to Machine Learning with Python – Andreas Muller and Sarah Guido
跟着本书配套的,还有一个 YouTube 视频,请点击这里。
2.4 书籍列表,来自 Github
3.1 Luis Serrano –A friendly Introduction to Machine Learning
3.2 Roshan – Machine Learning – Video Series
3.3 Machine Learning with Scikit-Learn (Scipy 2016) – Part 1 and Part 2
3.4 Machine Learning with Python – Sentdex Playlist
3.5 Machine Learning with Scikit-Learn – Cristi Vlad Playlist
3.6 Machine Learning APIs by Example – Google Developers
3.7 Practical Introduction to Machine Learning – Same Hames
3.8 Machine Learning Recipes – with Josh Gordon
4.1 Machine Learning 101 – from BigML
4.2 Learning Machine Learning – EliteDataScience
4.3 Top-down learning path: Machine Learning for Software Engineers
4.4 Machine Learning Mastery – by Dr. Jason Brownlee
请记住,为了更好的学习,我建议你一次不要学习太多的知识,天天话几小时就行了,而后请记住一点,好好享受睡觉,良好的睡眠对学习相当重要。
做者:chen_h
微信号 & QQ:862251340
博客地址:http://www.jianshu.com/p/5084...
CoderPai 是一个专一于算法实战的平台,从基础的算法到人工智能算法都有设计。若是你对算法实战感兴趣,请快快关注咱们吧。加入AI实战微信群,AI实战QQ群,ACM算法微信群,ACM算法QQ群。长按或者扫描以下二维码,关注 “CoderPai” 微信号(coderpai)