Python机器学习教程资料/代码

摘要

转自：爱可可-爱生活

This tutorial will teach you the basics of scikit-learn. I will give you a brief overview of the basic concepts of classification and regression analysis, and how to build powerful predictive models from labeled data. Although it's not a requirement for attending this tutorial, I highly recommend you to check out the accompanying GitHub repository at https://github.com/rasbt/msu-datascience-ml-tutorial-2018 1-2 days before the tutorial. During the session, we will not only talk about scikit-learn, but we will also go over some live code examples to get the knack of scikit-learn's API.

If you have any questions about the tutorial, please don't hesitate to contact me. You can either open an "issue" on GitHub or reach me via email at mail_at_sebastianraschka.com. I am looking forward to meeting you soon!

View the presentation slides: https://speakerdeck.com/rasbt/machine-learning-with-python

View the code notebook: code/tutorial.ipynb

Schedule

This repository will contain the teaching material and other info for theLearning scikit-learntutorial at theMSU Data Scienceheld on February 21st 6:15-7:30 pm at Wells Hall (WH) B102.

When?Wed Feb 21, 2018 at 6:15 - 7:30 pm

Where?Michigan State University Wells Hall (WH) B102

I recommend watching the MSU Data Science website and Facebook group for (last minute) updates

http://msudatascience.com/calendar/

https://www.facebook.com/events/174671933295040/

Obtaining the Tutorial Material

If you already have a GitHub account, the probably most convenient way to obtain the tutorial material is to clone this GitHub repository via and fetch updates via

链接：

https://github.com/rasbt/msu-datascience-ml-tutorial-2018

原文链接：

https://m.weibo.cn/1402400261/4210319288766371