888102-student

888102 Big Data Analytics – Chapter 10, 11 and 12 Materials

International College of Digital Innovation, Chiang Mai University.

Each part of a chapter is one notebook: the lesson, the worked examples in code, a real dataset, and the graded homework. Open a part in Colab and run it – nothing to install.

Chapter 10 – Supervised Learning

Part Hands-on notebook
10.1 Classification with Decision Trees Open in Colab
10.2 Evaluating a Classifier Open in Colab
10.3 Regression Open in Colab

Chapter 11 – Unsupervised Learning

Part Hands-on notebook
11.1 Unsupervised Learning and Clustering Open in Colab
11.2 Association Rules and Market Basket Analysis Open in Colab

The Chapter 11 hands-on session, where the code runs on the slides in the browser, is at https://payakorn.github.io/888102-student/hands-on/ch11_Hands_On_Unsupervised_Learning.html

Chapter 12 – Text Mining and Sentiment Analysis

Part Hands-on notebook
12.1 Text Mining and the Bag of Words Open in Colab
12.2 Standard Sentiment Analysis Open in Colab
12.3 Types of Sentiment Analysis and the Business Insight Open in Colab

Each part has a hands-on session where the code runs on the slides in the browser:

All hands-on sessions are listed at https://payakorn.github.io/888102-student/hands-on/

How to use them

Sign in to Google, open a part from the table above, then File -> Save a copy in Drive so your work is kept. Run the cells in order: a later cell uses variables made by earlier ones. The first code cell imports numpy, pandas and matplotlib (Chapter 11.2 needs only pandas; Chapters 12.2 and 12.3 install the VADER sentiment package the first time it runs in Colab).

Every notebook already carries its outputs, so you can read a part before running anything, and check your own results against it afterwards.

You can also browse them at https://colab.research.google.com/github/payakorn/888102-student and pick a notebook from the file browser.

Getting the files locally

git clone https://github.com/payakorn/888102-student.git