Lecture 1: Introduction and Optimization Problems

Update: 2017-05-10

Description

Prof. Guttag provides an overview of the course and discusses how we use computational models to understand the world in which we live, in particular he discusses the knapsack problem and greedy algoriths.

Comments

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Lecture 15: Statistical Sins and Wrap Up

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Lecture 14: Classification and Statistical Sins

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Lecture 13: Classification

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Lecture 12: Clustering

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Lecture 11: Introduction to Machine Learning

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Lecture 10: Understanding Experimental Data (cont

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Lecture 9: Understanding Experimental Data

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Lecture 8: Sampling and Standard Error

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Lecture 7: Confidence Intervals

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Lecture 6: Monte Carlo Simulation

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Lecture 5: Random Walks

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Lecture 4: Stochastic Thinking

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Lecture 3: Graph-theoretic Models

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Lecture 2: Optimization Problems

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Lecture 1: Introduction and Optimization Problems

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Lecture 1: Introduction and Optimization Problems

#box-pro-ellipsis-176175028619149{-webkit-line-clamp:2;}Lecture 1: Introduction and Optimization Problems

Lecture 1: Introduction and Optimization Problems

John Guttag

Lecture 1: Introduction and Optimization Problems