Getting Lots of Data and Artificial Data

Loading...
Stanford University
4.9 (114,162 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 (114,162 ratings)
  • 5 stars
    105,742 ratings
  • 4 stars
    7,761 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
Application Example: Photo OCR
Identifying and recognizing objects, words, and digits in an image is a challenging task. We discuss how a pipeline can be built to tackle this problem and how to analyze and improve the performance of such a system.

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.