Created by:  Stanford University

  • Andrew Ng

    Taught by:  Andrew Ng, Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain

Language
English, Subtitles: Spanish, Hindi, Japanese, Chinese (Simplified)
How To PassPass all graded assignments to complete the course.
User Ratings
4.9 stars
Average User Rating 4.9See what learners said
Syllabus

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Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Creators
Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Ratings and Reviews
Rated 4.9 out of 5 of 45,387 ratings

very goodddddddddd!!非常好的一门课

This was the best course ever :D

fantastic course!

I should have never hesitated to take this course. It seems to me that anyone who is serious about learning machine learning (outside of a more structured environment such as a university program) absolutely must start with this course. With a tenuous grasp on Python, I am still not ecstatic about this course's use of Octave, but as others have said, one should not be deterred by this. And even though this course does not touch on all of the significant ML methods (e.g., random forests), it definitely delves (a purposefully chosen verb, mind you) into perhaps the most significant. Of note, the transition from one-versus-all logistic regression to neural networks was masterful. And while the dive into neural networks was unexpected for an 'introductory' course on machine learning, it was tremendously gratifying to learn (more than just the basics) about something that has only grown more prominent since the inception of this course. To cut to it, Dr. Ng is clearly a gifted, fantastic instructor. The balance of mathematics in this Coursera version of the course was perfect. I loved learning the mathematical meat of the algorithms and, and the same, *not* having to grapple with unnecessary proofs and the like. I feel deeply privileged to have been able to work through this course. And I am excited that Dr. Ng has now released a new specialization on deep learning (using Python, no less!). Thank you!