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Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

TeX 0.54% Jupyter Notebook 99.46%

stat479-machine-learning-fs19's Issues

Decision trees lecture note: Page 13

Typo:
6.10.1 Grain Ratio should be Gain Ratio
6.10.1 first-line: gain ration : n is extra

Typo: Ensembles lecture note: section 7.4: Bagging Page 4

In a nutshell, a "boostrap" sample
should be "bootstrap"

Python resource

Hi there! I came across this course via your twitter post - it looks fantastic!

I teach a machine learning course for high school students through MIT, and ended up developing my own resources for ramping up students in Python. It looks like you have similar needs towards this end, so I figured I would point you to my material: Python Like You Mean It

The material includes worked reading comprehension questions, and has proven to be pretty popular with students going into ML/data science. It seems to be quite in line with your needs (i.e. installing Python with anaconda, environment management, introducing jupyter notebooks, covering the essentials of numpy, etc.). I hope that you find it useful!

P.S. there are no ads on the site or anything of that sort - this is not me trying to make a buck :)

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