Intro to Data Science and Machine Learning in Python

Notebooks and supporting files for the "Intro to Data Science and Machine Learning in Python" workshop.

Linear Regression

A simple example of linear regression in scikit learn using the diabetes dataset.

Logistic Regression

An example of logistic regression in scikit learn using the breast cancer dataset. Includes a short exercise.

Clustering

A demonstration of k-means clustering showing the effect of the parameter k and how it deals with bad initialization.

Trees

An example of decision trees with a diagram of a tree that has been learned.

Ensemble Methods

Demonstrations of three ensemble approaches:

1. Bagging
2. Random forest
3. Gradient boosting

Dimensionality Reduction

A short demonstration of PCA

Applying Dimensionality Reduction to Improve Clustering

This exercise takes you through using T-SNE to enhance the performance of k-means while also providing the ability to easily visualize complex multidimensional data.

Further Exploration

Linear Algebra Basics

A brief overview of some essential linear algebra, including summation and dot-products

Scorecard

An example of a machine learning process using a fairly realistic scenario: financial credit scoring