Choosing the learning rate

video-placeholder
Loading...
Просмотреть программу курса

Получаемые навыки

Regularization to Avoid Overfitting, Gradient Descent, Supervised Learning, Linear Regression, Logistic Regression for Classification

Рецензии

4.9 (оценок: 3,990)

  • 5 stars
    91,32 %
  • 4 stars
    7,79 %
  • 3 stars
    0,55 %
  • 2 stars
    0,12 %
  • 1 star
    0,20 %

KY

8 сент. 2022 г.

Professor Andrew can explain complex knowledge clearly. The Python lab can help learner to understand algorithm. The course is more valuable. I am excited to learn the next course for advanced ML.

YD

2 окт. 2022 г.

Excellent course. Intended as a refresher, and had a better understanding of feauture engineering, scaling, and logistic regression. Good hands on labs were very practical, engaging and rewarding.

Из урока

Week 2: Regression with multiple input variables

Преподаватели

  • Placeholder

    Andrew Ng

    Instructor

  • Placeholder

    Eddy Shyu

    Curriculum Architect

  • Placeholder

    Aarti Bagul

    Curriculum Engineer

  • Placeholder

    Geoff Ladwig

    Curriculum Engineer

Ознакомьтесь с нашим каталогом

Присоединяйтесь бесплатно и получайте персонализированные рекомендации, обновления и предложения.