Welcome to the repository for the An Introduction to Machine Learning course (formally 'Intro to Machine Learning in Python' delivered by in 2023 and 2024). This course is aimed at providing an introduction to machine learning covering:
- What Is Machine Learning and A Recap of Exploratory Data Analysis (EDA)
- Classification Basics and Logistic Regression
- More Classification Models (Decision Trees and k-NN)
- Regression and Practical Considerations in ML
This course will be available for participants to engage in either R or Python. It is therefore expected that those taking this course have some beginner level of either Python or R (as offered in the Introduction to Python or Introduction to R CDCS courses).
The materials in this repo are most recently adapted by Chris Oldnall (with original resources by Bhargavi Ganesh). All material collected here is free to use but is covered by a License: 
Throughout this course we will be using the Noteable platform to run Jupyter notebooks. This is a cloud-based computational notebook system that work on your browser from any device.
- Open the following link in a new tab: https://noteable.edina.ac.uk/login.
- Login with your EASE credentials (either your Edinburgh university login, or those you were provided with).
- Under 'Standard Notebook (Python 3)' click 'Start'
- From the Noteable home page, click on the '+GitRepo' button at the top right of the screen.
- In the 'Git Repository URL' field copy the link to this GitHub repository, "https://github.com/DCS-training/machine_learning_python". Ignore all other fields.
- Once filled in, click the 'clone' button. After a few moments, you will then see a new folder appear with the files.