Features and Polynomial Regression

Loading...
シラバスを表示

学習するスキル

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

レビュー

4.9 (114,290 件の評価)
  • 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)

レッスンから
Linear Regression with Multiple Variables
What if your input has more than one value? In this module, we show how linear regression can be extended to accommodate multiple input features. We also discuss best practices for implementing linear regression.

講師

  • 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

コース一覧で検討

サインアップは無料です。今すぐサインアップして、パーソナライズされたお勧め、更新、サービスを利用しましょう。