Machine Learning & Data Analytics

Photo by Edgar Chaparro on Unsplash

Overview

The objective of this module is to provide a real-world scenario in which you can practice the following data science / machine learning skills:

• Assessing Data Quality
• Investigating Feature Relationships
• Scaling and Normalization
• Ethics
• Unsupervised Learning and K-Means Clustering

Preparation Reading

Complete the following preparation reading:

• Read sections 3.1, 3.2, 3.3, 3.4, and 3.6 of your text. (You've already read section 3.5, but feel free to review it.)

• Watch the following introduction to Cluster Analysis:

• Read about the Sci-Kit Learn implementation of K-Means clustering.

• Review the Sci-Kit Learn API docs for K-Means clustering

• Read this article: Top three mistakes with K-Means Clustering during data analysis

• Read this article: K-means clustering is not a free lunch