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3: Classification

Date: 1st November 2023

πŸ’‘ Classification helps us to group data into predefined classes. Logistic Regression is a linear model used for binary classification, while K-means is an unsupervised clustering algorithm that categorizes data into clusters. Support Vector Machines (SVM) find an optimal hyperplane to separate data, and Decision Trees use a tree-like structure to make decisions based on feature attributes. Come to this session to explore and implement these four well-known classification methods! πŸ’‘

You can access our demonstration notebook here: πŸ“˜ Tutorial 3 Notebook

The folder contains notebooks for Logistic Regression, SVMs, Decision Trees and K-Means. The solutions are available in the same folder.

You can access our slides here: πŸ’» Tutorial 3 Slides

The recording from this session is available here: 🎀 Tutorial 3 Recording

The DOXA Challenge notebook can be found here: πŸ† DOXA Challenge 1

This is now open for submissions! Let's see how well your models can performπŸ™ŒπŸΌ

This is the end of the Classical Machine Learning section of the series. We will continute next half term on Deep Learning πŸ₯³

Hope you have a great reading week! Please join our WhatsApp group chat through this link.