The Problem of Overfitting

Loading...
Eye
斯坦福大学
4.9(114,290 個評分) | 2.5M 名學生已註冊
查看授課大綱

您將學習的技能

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

審閱

4.9(114,290 個評分)
  • 5 stars
    105,856 ratings
  • 4 stars
    7,774 ratings
  • 3 stars
    489 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)

從本節課中
Regularization
Machine learning models need to generalize well to new examples that the model has not seen in practice. In this module, we introduce regularization, which helps prevent models from overfitting the training data.

教學方

  • 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

探索我們的目錄

免費加入並獲得個性化推薦、更新和優惠。