Gradient Descent in Practice II - Learning Rate

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Получаемые навыки

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

Рецензии

4.9 (оценок: 156,021)
  • 5 stars
    92.44%
  • 4 stars
    6.89%
  • 3 stars
    0.45%
  • 2 stars
    0.08%
  • 1 star
    0.11%
FG
20 июля 2019 г.

Exceptionally complete and outstanding summary of main learning algorithms used currently and globally in software industry. Professor with great charisma as well as patient and clear in his teaching.

OK
17 апр. 2018 г.

You need to know, what do you want to get out of this course. It gives you a lot of information, but be prepared to work hard with linear algeabra and make efforts to compute things in Mathlab/Octave.

Из урока
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.

Преподаватели

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    Andrew Ng

    Instructor

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