CS 229 * We aren't endorsed by this school

CS 229 MACHINE LEARNING

  • Average Course Rating (from 2 Students)

    4.5/5
    Overall Rating Breakdown
    • 2 Advice
    • 5
      50%
    • 4
      50%
    • 3
      0%
    • 2
      0%
    • 1
      0%
  • Course Difficulty Rating

    • Easy 0%

    • Medium 50%

    • Hard 50%

  • Top Course Tags

    Math-heavy

    Background Knowledge Expected

    Go to Office Hours

* We aren't endorsed by this school

MACHINE LEARNING Questions & Answers

MACHINE LEARNING Flashcards

MACHINE LEARNING Advice

MACHINE LEARNING Documents

Showing 1 to 30 of 541

Sort by:
{[$select.selected.label]}

Recent Documents


MACHINE LEARNING Questions & Answers


MACHINE LEARNING Advice

Showing 1 to 2 of 2

View all
    • Profile picture
    Feb 09, 2016
    | Would highly recommend.

    Not too easy. Not too difficult.

    Course Overview:

    I strongly recommend the course. It covers most modern topics on machine learning. It not only introduces the algorithms themselves but also the mathematics and intuitions behind them. The proofs are very rigorous. They are definitely helpful both for a job interview and for research purporse (as a starting point).

    Course highlights:

    The best part is that Andrew gives us not only the knowledge but also the precious experience he got from so many year's research and work.

    Hours per week:

    3-5 hours

    Advice for students:

    Be sure to derive the algorithms by yourself offline.

    • Fall 2016
    • ANDREWNG
    • Math-heavy Group Projects Requires Presentations
    • Profile picture
    Jan 06, 2017
    | Would recommend.

    This class was tough.

    Course Overview:

    This is a great introductory course in machine learning, but covers a lot more material than required for a basic course. You can get lost pretty quickly if you don't follow the lectures closely; you might feel like they have cramped way too many topics for one quarter. But if you're interested, go ahead, it's a wonderful course!

    Course highlights:

    Andrew Ng really gives an intuitive perspective for most topics. Unsupervised learning techniques were the highlight.

    Hours per week:

    9-11 hours

    Advice for students:

    Be prepared to do a lot of math; proving theorems is a major part of the course. Your linear algebra skills will be very important for this subject, so make sure you brush up on those before taking it.

    • Fall 2016
    • Andrew NG
    • Math-heavy Background Knowledge Expected Go to Office Hours

Ask a homework question - tutors are online