Stochastic Gradient Descent

Loading...
Eye
Stanford University
4.9 (114,252 ratings) | 2.5M Students Enrolled
View Syllabus

Skills You'll Learn

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

Reviews

4.9 (114,252 ratings)
  • 5 stars
    105,822 ratings
  • 4 stars
    7,771 ratings
  • 3 stars
    488 ratings
  • 2 stars
    83 ratings
  • 1 star
    88 ratings
ML

Aug 19, 2017

Very helpful and easy to learn. The quiz and programming assignments are well designed and very useful. Thank Prof. Andrew Ng and coursera and the ones who share their problems and ideas in the forum.

CC

Jun 20, 2018

good course; just 2 suggestions: improve the skew data part (week 6) and furnish the formula to evaluate the number of iteration in the window from image dimension, window dimension and step (week 11)

From the lesson
Large Scale Machine Learning
Machine learning works best when there is an abundance of data to leverage for training. In this module, we discuss how to apply the machine learning algorithms with large 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.