Workshops
Applied Intro to Machine Learning

Applied Intro to Machine Learning

This workshop will cover some of the tools and workflow for getting started with applied ML. Attendees will learn how to use jupyter notebooks, and the scientific python ecosystem to experiment with machine learning.

Learning outcomes

Prerequisites

This workshop assumes:

Set up instructions

The easy way

The easy way of getting everything you need for this workshop is by the way of installing Anaconda.

The less easy way

Alternatively, you can manually install the following components.

Contributors: Tom Brady, Tom Read Cutting
Thanks to: Jared Khan
View code examples on GitHub
License: BSD-3-Clause

Applied Intro to Machine Learning Workshop

This repository will present an applied introduction to machine learning.

Applied example which shows, via a Jupyter notebook:

Getting started

Grabbing the Machine learning code

The majority of this workshop will be taught through the use of a Jupyter notebook, which you can download from here. Everything you need is in the examples folder.

Alternatively, you can clone the repository using Git:

git clone https://github.com/hackersatcambridge/workshop-python-ml

Further reading