subject
Intro

Learning from Data (Introductory Machine Learning course)

 with  Yaser Abu-Mostafa

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures below follow each other in a story-like fashion:

  • What is learning?
  • Can a machine learn?
  • How to do it?
  • How to do it well?
  • Take-home lessons.

Syllabus

 

 

8 Student
reviews
Cost Free Online Course
Pace Self Paced
Provider Independent
Language English
Calendar 10 weeks long
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FAQ View All
What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

8 reviews for Learning from Data (Introductory Machine Learning course)

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11 out of 11 people found the following review useful
2 years ago
Hchan completed this course, spending 12 hours a week on it and found the course difficulty to be hard.
The best online machine learning course I've taken (I've completed courses by Andrew Ng as well as Hastie and Tibshirani et al), this course covers rigorous theory as well as practical aspects, setting you up for a very solid foundation for future study in machine learning. Assignments are challenging and really requir Read More
The best online machine learning course I've taken (I've completed courses by Andrew Ng as well as Hastie and Tibshirani et al), this course covers rigorous theory as well as practical aspects, setting you up for a very solid foundation for future study in machine learning. Assignments are challenging and really require you to understand and engage with the material. Prof Abu-Mostafa's teaching quality is amazing and even highly complex concepts are clearly presented.
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a year ago
Asr completed this course.
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7 months ago
Lars Ahlfors completed this course.
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3 months ago
Ronny De Winter completed this course.
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0 out of 7 people found the following review useful
2 years ago
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Rafael Prados completed this course.
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0 out of 3 people found the following review useful
2 years ago
Colin Khein completed this course.
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