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Machine Learning

6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and ...

Start Date: Sep 01, 2006 Topics: Machine Learning
Cost: Free

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Overview

Description

6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.

Details

  • Dates: Sep 01, 2006 to Dec 20, 2006
  • Days of the Week: Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday
  • Level of Difficulty: Beginner
  • Size: Massive Open Online Course
  • Instructors: Ali Mohammad, Prof. Tommi Jaakkola, Rohit Singh
  • Cost: Free
  • Institution: MIT OCW
  • Topics: Machine Learning

Provider Overview

About MIT OCW: MIT OpenCourseWare (OCW) is a web-based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity.

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