In this week, you will learn basic concepts about machine learning, including the basic Python libraries that we will use repeatedly throughout this course. This includes learning how to use scikit learn to perform different types of machine learning as well as the scikit learn (sklearn) and statsmodel libraries to perform regression. We also will explore the important, and often overlooked task, of data pre-processing. This includes handling missing or invalid data, computation of dates, and understanding the data provenance.
- Know the basics concepts that underlie machine learning.
- Understand the importance of data preparation to enable a successful machine learning analysis.
- Understand the basic concepts of linear regression.
| Activities and Assignments | Time Estimate | Deadline* | Points |
|---|---|---|---|
| Week 1 Introduction Video | 10 Minutes | Tuesday | NA |
| Week 1 Lesson 1: Intro to Machine Learning | 2 Hours | Thursday | 20 |
| Week 1 Lesson 2: Machine Learning: Pre-processing | 2 Hours | Thursday | 20 |
| Week 1 Lesson 3: Introduction to Linear Regression | 2 Hours | Thursday | 20 |
| Week 1 Quiz | 45 Minutes | Friday | 70 |
*Please note that unless otherwise noted, the due time is 6pm Central time!