Advanced Quantitative Research

Course Materials

01 Introduction
02 Randomized Trials
03 Instrumental Variables
04 Regression Discontinuity
05 DiD 1: Standard DiD
06 DiD 2: Synthetic Control
07 DiD 3: Time Variant
08 ML 1: Intro to Machine Learning
09 ML 2: Classification
10 ML 3: Regression
11 Factor Analysis
12 ML 4: Unsupervised
13 ML 5: Intro to NLP

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Important Optional

# Module 12

Unsupervised Learning

Learning Objectives: Understand the differences between supervised and unsupervised learning. Implementation of K-means clustering. A contextual understanding of neural networks.

Before the Class

Unsupervised Learning

CrashCourse, "Unsupervised Learning: Crash Course AI #6"

Neural Networks

CrashCourse, "Neural Networks and Deep Learning: Crash Course AI #3"

Course Materials

Students are encouraged to read and watch the items under Before the Class Use the icons below to determine whether a reading is important or optional:

Unsupervised Learning

Unsupervised Learning

Neural Networks

Students are encouraged to read and watch the items under Before the Class
Use the icons below to determine whether a reading is important or optional: