isabeldepapel/wwc-workshop-intro-to-machine-learning

Women Who Code Workshop: Intro to Machine Learning in Python

Preparation for the Workshop

We will be using Python and Jupyter Notebook to navigate through our code. The installation process is much easier for mac users, but we'll do our best to get you up and running on a PC. If you aren't able to follow the instructions below you can follow along with the Lecture Notes on github and trouble-shoot later.

Download and Install Anaconda

Anaconda is a an open source package management software that allows you to easily install many of the Python libraries we will be using (and more!!). You can download Anaconda here: https://www.anaconda.com/download/ We'll be using version 2.7, but you are welcome to download later versions. There will be some syntactical differences but they are more or less the same.

Launch a Jupyter Notebook

In your terminal window, type 'Jupyter Notebook' into the command line. It should launch a new browser window pointing to whatever folder you were already in. If it doesn't copy and paste the localhost url into a new browser window.

Setup a Github account (optional)

The workshop notes and datasets we'll be working with are all on Github. You don't need an account to view the notes or download the whole repo to your local drive. However there are many benefits to using GitHub (including version control), so if you want to make changes to the code and save a version of it online, you will need your own account. Follow the instructions here: https://github.com/join?source=header-repo

Pre-workshop Checklist

At the beginning of the workshop you should have:

• Anaconda installed
• GitHub Account created (optional)
• Jupyter Notebook launched

Instructions for Saturday

Fork the Lecture Notes Repository (optional)

If you plan to push changes to GitHub you'll need your own forked version! In the upper right hand corner of this repo, click "Fork." Again, if you've never done this GitHub has solid documentation to help walk you through forking: https://help.github.com/articles/fork-a-repo/

Clone this repo to your local drive

If you've already forked the repo you can skip this step. If you chose not to create your own github account, you can clone the repo directly to your local drive and work with the files that way. On the right-side of your screen click the green button that says "clone or download." Follow along with these instructions: https://help.github.com/articles/cloning-a-repository/

Introduction

In this hands-on workshop, we'll walk through the basic steps of building a predictive model in Python. At the end of the workshop you'll be able to:

1. Understand the basic principles of Machine Learning
2. Identify appropriate models for classification and regression problems
3. Use Scikit-Learn to train and evaluate models
4. Know where to turn for additional resources Happy Coding!