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Online Course

Fundamentals of Machine Learning

Santa Fe Institute via Complexity Explorer

Overview

Machine Learning is a fast growing, rapidly advancing field that touches nearly everyone's lives. There has recently been an explosion of successful machine learning applications - in everything from voice recognition to text analysis to deeper insights for researchers. While common and frequently talked about, most people have only a vague concept of how machine learning actually works.

In this tutorial, Dr. Artemy Kolchinsky and Dr. Brendan Tracey outline exactly what it is that makes machine learning so special in an accessible way. The principles of training and generalization in machine learning are explained with ample metaphors and visual intuitions, an extended analysis of machine learning in games provides a thorough example, and a closer look at the deep neural nets that are the core of successful machine learning. Finally, it addresses when it's appropriate to use (and not use) machine learning in problem solving, as well as an example of scientific research incorporating machine learning principles.

Students of all levels should be able to follow this reasonably-paced introduction to one of the most important engineering breakthroughs of our time.

 

Syllabus

  1. Types of Machine Learning
  2. A Geometric View of Supervised Learning
  3. Generalization Performance
  4. Artificial Intelligence and Board Games
  5. Go as a Supervised Learning Problem
  6. Fundamentals of Game-Playing Systems
  7. Building a Go Machine Learning Program
  8. Introduction to Neural Networks
  9. Why do Deep Neural Networks Succeed?
  10. The Mystery of Deep Learning
  11. Some Caveats of Using Machine Learning
  12. Advanced Concepts: Stacked Monte Carlo
  13. Homework

 

Taught by

Brendan Tracey and Artemy Kolchinsky

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Reviews

4.6 rating, based on 5 reviews

Start your review of Fundamentals of Machine Learning

  • Profile image for Mauricio Rada
    Mauricio Rada

    Mauricio Rada completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    Very well structured with the seal of the Santa Fe Institute. It's a good qualitative and intuitive introduction to anyone interested on machine learning in just some classes. I recommend it.
  • Anonymous

    Anonymous completed this course.

    It's wonderful! It took a couple of hours to finish the course. Now I know the basics of Machine Learning and how computers are winning the Chess and Go games.

    Thank you very much!
  • Anonymous

    Anonymous completed this course.

    This is a broad and yet not overwhelming introduction to the fascinating history and technical aspects of Machine Learning. Both with the excelent video content provided and the self-paced structure of the course proves to be an interesting heads on approach to this science. Don't expect many exercises with the actual algorithms or heavy coding though; that, you'll have to do on your own with the concepts provided.
  • Anonymous

    Anonymous completed this course.

    This course gave me an good overview on the field, explaining the most outstanding topics in a brief and most of the time, not complicated way. I would add more supplementary material as reference and also guidance towards more advanced training
  • Abhijit Borah

    Abhijit Borah completed this course, spending 1 hours a week on it and found the course difficulty to be medium.

    I wish there a module where we are taught to make simple codes. The introductory exposure was satisfying for a first time learner like me. I wish the course gets expanded.

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