The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.

Dates:

- Free schedule

Included in selections:

Machine Learning

Machine learning: from the basics to advanced topics. Includes statistics...

Machine learning: from the basics to advanced topics. Includes statistics...

More on this topic:

Machine Learning

Why write programs when the computer can instead learn them from data? In this...

Why write programs when the computer can instead learn them from data? In this...

Graph Partitioning and Expanders

The Course In this research-oriented graduate course, we will study algorithms...

The Course In this research-oriented graduate course, we will study algorithms...

Data Organization - Learn Big Data Management - Udemy

Infrastructure, Algorithms, and Visualizations

Infrastructure, Algorithms, and Visualizations

Language Acquisition I

Lectures, reading, and discussion of current theory and data concerning the...

Lectures, reading, and discussion of current theory and data concerning the...

Introduction to Computational Neuroscience

This course gives a mathematical introduction to neural coding and dynamics...

This course gives a mathematical introduction to neural coding and dynamics...

More from 'Mathematics, Statistics and Data Analysis':

Business Analytics for Data-Driven Decision Making

Learn how to lead your firm to make better business decisions using analytic...

Learn how to lead your firm to make better business decisions using analytic...

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD

This course takes you through roughly five weeks of MATH 1554, Linear Algebra...

This course takes you through roughly five weeks of MATH 1554, Linear Algebra...

Manufacturing Systems I

Learn about manufacturing systems and ways to analyze them in terms of material...

Learn about manufacturing systems and ways to analyze them in terms of material...

Manufacturing Process Control II

Learn how to control process variation, including methods to design experiments...

Learn how to control process variation, including methods to design experiments...

Multidisciplinary Research methods for Engineers

Engineering is no longer limited to working in a single domain; nowadays engineers...

Engineering is no longer limited to working in a single domain; nowadays engineers...

More from 'MIT OpenCourseWare':

Introduction to Computers and Engineering Problem Solving

This course presents the fundamentals of object-oriented software design and...

This course presents the fundamentals of object-oriented software design and...

Uncertainty in Engineering

This course gives an introduction to probability and statistics, with emphasis...

This course gives an introduction to probability and statistics, with emphasis...

Project Evaluation

1.011 Project Evaluation covers methodologies for evaluating civil engineering...

1.011 Project Evaluation covers methodologies for evaluating civil engineering...

Introduction to Civil Engineering Design

1.012 introduces students to the theory, tools, and techniques of engineering...

1.012 introduces students to the theory, tools, and techniques of engineering...

Computing and Data Analysis for Environmental Applications

This subject is a computer-oriented introduction to probability and data analysis...

This subject is a computer-oriented introduction to probability and data analysis...

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