
MIT OpenCourseWare
A free and open online publication of educational material from thousands of MIT courses, covering the entire MIT curriculum, ranging from introductory to the most advanced graduate courses. On the OCW website, each course includes a syllabus, instructional material like notes and reading lists, and learning activities like assignments and solutions. Some courses also have videos, online textbooks, and faculty insights on teaching. Knowledge is your reward. There's no signup or enrollment, and no start or end dates. OCW is self-paced learning at its best. Whether you’re a student, a teacher, or simply a curious person that wants to learn, MIT OpenCourseWare (OCW) offers a wealth of insight, inspiration, videos, and a whole lot more! Get the full picture on the OCW website at https://ocw.mit.edu. Accessibility: https://accessibility.mit.edu/ User comments policy: https://ocw.mit.edu/comments/ (Channel banner photo by Nietnagel on Flickr: https://flic.kr/p/8WXxfK.)
Episodes


8.2.1 An Introduction to Linear Optimization - Video 1: Introduction

2.4.4 R2. Moneyball in the NBA - Video 3: Points Scored

6.2.7 An Introduction to Clustering - Video 4: Computing Distances

3.3.1 The Framingham Heart Study - Video 1: Evaluating Risk Factors to Save Lives

4.2.9 An Introduction to Trees - Video 5: Random Forests

7.2.7 An Introduction to Visualization - Video 4: Basic Scatterplots Using ggplot

4.3.17 Healthcare Costs - Video 9: Results

2.2.9 An Introduction to Linear Regression - Video 5: Understanding the Model

5.4.8 R5. Predictive Coding - Video 7: The ROC Curve

4.4.2 R4. Regression Trees - Video 1: Boston Housing Data

2.2.3 An Introduction to Linear Regression - Video 2: One-variable Linear Regression

8.2.6 An Introduction to Linear Optimization - Video 4: Solving the Problem

7.3.1 Visualization for Law and Order - Video 1: Predictive Policing

1.4.6 R1. Understanding Food - Video 5: Adding Variables

9.3.1 eHarmony - Video 1: The Goal of eHarmony

6.2.15 An Introduction to Clustering - Video 8: The Analytics Edge of Recommendation Systems

9.3.5 eHarmony - Video 3: Predicting Compatibility Scores

1.4.3 R1. Understanding Food - Video 2: Working with Data in R

2.3.5 Sports Analytics - Video 3: Predicting Runs
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