Reading 11: Introduction to Machine Learning

Reading 11: Introduction to Machine Learning#

For the class on Monday, March 11th

Reading assignments#

  1. Read the following sections of [Acq23]:

    • Chap. 1 “Introduction to Machine Learning Methods”

      • Sec. 1.1 “What Is Machine Learning?”

      • Sec. 1.2 “What Can We Do with It?”

      • Sec. 1.3 “The Language of Machine Learning”

      • Sec. 1.4 “Supervised Learning”

      • Sec. 1.5 “Unsupervised Learning”

      • Sec. 1.6 “Machine Learning versus Inference”



Submit your answer on Canvas. Due at noon, Monday, March 11th.

  1. List anything from your reading that confuses you. Explain why they confuse you. If nothing confuses you, briefly summarize what you have learned from this reading assignment.

  2. What is the main difference between a supervised learning method and a unsupervised learning method?

  3. What is the main difference between a machine learning method and a statistical inference method?

Discussion Preview#


We will discuss the following questions in class. They are included here so that you have a chance to think about them before class. You need not submit your answers as part of this assignment.

  1. What are the definitions of the four major categories of machine learning methdos: clustering, dimensionality reduction, regression, and classification? In what situations is each of these methods useful?

  2. What are the pros and cons of applying machine learning methods in physics and astronomy? When should one use machine learning methods instead of statistical inference methods?