Multiple Features

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Stanford University
4.9 (121,650 ratings) | 2.7M Students Enrolled
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Skills You'll Learn

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

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4.9 (121,650 ratings)
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NN

Oct 15, 2016

It's a good introduction - not too complicated and covers a wide range of topics. The programming exercises are well put together and significantly help understanding. The free Matlab license is nice.

PT

Sep 01, 2018

Sub title should be corrected. Since I'm not that good in English but I know when there're mis-traslated or wrong sub title. If you fix this problems , I thin it helps many students a lot. Thanks!!!!!

From the lesson
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.

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

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