Gradient Descent for Multiple Variables

Loading...
강의 계획서 보기

배우게 될 기술

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

검토

4.9(119,588개의 평가)
  • 5 stars
    110,737 ratings
  • 4 stars
    8,158 ratings
  • 3 stars
    515 ratings
  • 2 stars
    87 ratings
  • 1 star
    91 ratings
SB

Sep 27, 2018

One of the best course at Coursera, the content are very well versed, assignments and quiz are quite challenging and good, Andrew is one of the best guide we could have in our side.\n\nThanks Coursera

MN

Oct 31, 2017

Great overview, enough details to have a good understanding of why the techniques work well. Especially appreciated the practical advice regarding debugging, algorithm evaluation and ceiling analysis.

수업에서
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.

강사:

  • 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

Coursera 카탈로그 살펴보기

무료로 참여해 맞춤화된 추천, 업데이트 및 제안을 받아보세요.