Choosing the Number of Principal Components

Loading...
Stanford University
4.9 (124,592 ratings) | 2.7M Students Enrolled
View Syllabus

Skills You'll Learn

Logistic Regression, Artificial Neural Network, Machine Learning (ML) Algorithms, Machine Learning

Reviews

4.9 (124,592 ratings)
  • 5 stars
    115,329 ratings
  • 4 stars
    8,533 ratings
  • 3 stars
    543 ratings
  • 2 stars
    90 ratings
  • 1 star
    97 ratings
PT

Sep 01, 2018

Sub title should be corrected. Since I'm not that good in English but I know when there're mis-traslated or wrong sub title. If you fix this problems , I thin it helps many students a lot. Thanks!!!!!

PM

Jul 14, 2019

This course is amazing and covers most of the ML algorithms. I really liked that this course has emphasized math behind each technique which helps to choose the best algorithm while solving a problem.

From the lesson
Dimensionality Reduction
In this module, we introduce Principal Components Analysis, and show how it can be used for data compression to speed up learning algorithms as well as for visualizations of complex datasets.

Taught By

  • Andrew Ng

    Andrew Ng

    CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.