Model Selection and Train/Validation/Test Sets

Loading...
Stanford University
4.9 (121,670 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 (121,670 ratings)
  • 5 stars
    112,652 ratings
  • 4 stars
    8,306 ratings
  • 3 stars
    528 ratings
  • 2 stars
    89 ratings
  • 1 star
    95 ratings
OK

Apr 18, 2018

You need to know, what do you want to get out of this course. It gives you a lot of information, but be prepared to work hard with linear algeabra and make efforts to compute things in Mathlab/Octave.

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
Advice for Applying Machine Learning
Applying machine learning in practice is not always straightforward. In this module, we share best practices for applying machine learning in practice, and discuss the best ways to evaluate performance of the learned models.

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.