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Stanford CS229: Machine Learning Course, Lecture 1 – Andrew Ng (Autumn 2018)

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Stanford Online

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2Ze53pq

Listen to the first lecture in Andrew Ng’s machine learning course. This course provides a broad introduction to machine learning and statistical pattern recognition. Learn about both supervised and unsupervised learning as well as learning theory, reinforcement learning and control. Explore recent applications of machine learning and design and develop algorithms for machines.

Andrew Ng is an Adjunct Professor of Computer Science at Stanford University. View more about Andrew on his website: https://www.andrewng.org/

To follow along with the course schedule and syllabus, visit:
http://cs229.stanford.edu/syllabus-autumn2018.html

05:21 Teaching team introductions
06:42 Goals for the course and the state of machine learning across research and industry
10:09 Prerequisites for the course
11:53 Homework, and a note about the Stanford honor code
16:57 Overview of the class project
25:57 Questions

#AndrewNg #machinelearning

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44 thoughts on “Stanford CS229: Machine Learning Course, Lecture 1 – Andrew Ng (Autumn 2018)”

  6. Hey Stanford!

    Sorry to interrupt, is the CS229 course syllabus currently down? I've been trying to gain access, in order to take a look at the problem sets, but unfortunately I keep encountering a 403 message, that simply states:

    "Forbidden:
    You don't have permission to access /syllabus-autumn2018.html on this server."

    Any help would be sincerely appreciated, cheers!

  10. the way this man teaches is something which doesn't get you tired. you will watch him teach with a beaming smile on your face.
    thanks for this great class.

  15. Heh. "Make democracy run better, instead of running worse." The problem with that is that most folks define "democracy running well" as "I get what I want." I don't think many people really step back and regard it as a system that's supposed to arrive at reasonable compromises among diverse points of view. If we did a better job of that we wouldn't be at each other's throats all the time.

  31. When I searched for ML I got this and saw Abdre Ng, I just cliked it instantly. I just now him in face and I knew when I was a 12th grader in 2018 G.C that he is a pretty recognized neural network scientist.

  36. Since he mentioned about the group project I naturally started think about who to work with on my group project but after he asked "How many of you this is your very first class at Stanford? raise your hand" I have realized I do not have any group project at Stanford. Wish I could be in there xd

  42. when he asked what percent of the class knew what supervised learning is to an intro ml class and 2/3 of the class raised their hand, i was like that's stanford for you

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