https://github.com/zkan/intro-to-machine-learning

Introduction to Machine Learning
https://github.com/zkan/intro-to-machine-learning

hacktoberfest machine-learning pandas python scikit-learn seaborn

Last synced: 8 days ago
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Introduction to Machine Learning

• Host: GitHub
• URL: https://github.com/zkan/intro-to-machine-learning
• Owner: zkan
• Created: 2015-04-11T03:30:26.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2020-03-02T12:42:35.000Z (almost 5 years ago)
• Last Synced: 2024-04-14T13:49:10.634Z (9 months ago)
• Topics: hacktoberfest, machine-learning, pandas, python, scikit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 967 KB
• Stars: 26
• Watchers: 5
• Forks: 10
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# Introduction to Machine Learning

The code in this repository is inspired by [Scikit

Learn](http://scikit-learn.org/) and [From Data With

Love](http://fromdatawithlove.thegovans.us/2013/05/clustering-using-scikit-learn.html).

## Installation Notes

This tutorial uses the following packages:

- Python version 2.7.6

- `numpy` version 1.9.2

- `scipy` version 0.15.1

- `matplotlib` version 1.4.3

- `scikit-learn` version 0.16.0

- `ipython` version 4.0.0, with notebook support (version 4.0.1)

You can also run `pipenv install` to install all required pacakges..

Alternatively, check [Installing

scikit-learn](http://scikit-learn.org/dev/install.html) out. It provides a good

instruction to get scikit-learn installed in different ways.

I also provide a `Vagrantfile` with a bootstrap script in case someone wants to

try on an Ubuntu box. However, please note that the Vagrant box doesn't support

any graphic stuff, so you'll need to remove or comment the code being used to

generate the plots before run the code.