Nearest Neighbour Algorithms
Nearest neighbour algorithms are useful for all kinds of problems. This python notebook explains what it is and how to use it.
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K-NN For Classification
We can use the nearest neighbour algorithm for classification too. This python notebook explains how to perform the k-Nearest Neighbours algorithm.
Overfitting and Underfitting
What is meant by a complex model? What does overfitting mean? All these questions are answered in this intuitive Python workshop.
Support Vector Machines
A python notebook demonstrating the use of support vector machines.
Logistic Regression
Logistic regression is very useful for producing probability estimates for classification. This simple workshop shows you how.
Linear Classification
We can also use linear models for classification purposes. Find out how in this workshop.
Regression: Dealing With Outliers
This workshop describes how you can perform regression when you are plagued by outliers.
Linear Regression
An introduction to regression with Python and SKLearn
Introduction to Gradient Descent
A Python workshop showing you why we need to optimise using gradient descent and provides a simple example.
Why Correlating Data is Bad and What to do About it
A Python Workshop explaining why correlating data is bad and what to do about it.
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