Methods, Techniques and Applications of Data Science

The following approaches fall into several larger categories that align with high-level functional steps in the practice of the data sciences:

• Data Collections
• Data Engineering
• Analytical Methods
• Reporting Methods
• Delivery Methods

We will use free data sets from the following sources in order to conduct our analysis:

• University of California at Irvine Machine Learning Repository
• Datahooked

The following are a list of the methods, techniques and applications in data science that I would like to cover this autumn and winter:

• Analysis of Variance (ANOVA)
• Feature Reduction through Methods Such as Principle Component Analysis (PCA)
• Classification Modeling & Prediction using AutoML
• Customer Segmentation via Cluster Analysis & Prediction