This lesson is in the early stages of development (Alpha version)

Introduction to Machine Learning with Scikit Learn

An introduction to machine learning.

Prerequisites

A basic understanding of Python. You will need to know how to write a for loop, if statement, use functions, libraries and perform basic arithmetic. Either of the Software Carpentry Python courses cover sufficient background.

Schedule

Setup Download files required for the lesson
00:00 1. Introduction What is machine learning?
00:40 2. Regression How can I make linear regression models from data?
How can I use logarithmic regression to work with non-linear data?
01:55 3. Introducing Scikit Learn How can I use scikit-learn to process data?
02:30 4. Clustering with Scikit Learn How can we use clustering to find data points with similar attributes?
03:05 5. Dimensionality Reduction How can we perform unsupervised learning with dimensionality reduction techniques such as PCA and TSNE?
03:05 6. Neural Networks How can we classify images using a neural network?
03:55 7. Ethics and Implications of Machine Learning What are the ethical implications of using machine learning in research?
04:10 8. Find out more Where can you find out more about machine learning?
04:20 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.