Chevron Left
返回到 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

学生对 DeepLearning.AI 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的评价和反馈

4.9
星
63,493 个评分

课程概述

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

热门审阅

AM

Oct 8, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

RR

Jun 12, 2020

Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

筛选依据：

4176 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 4200 个评论（共 7,283 个）

创建者 Abdillah F

•

Nov 10, 2020

The best deep learning course!!

创建者 Dirk P

•

Nov 8, 2020

Great pedagogical introduction!

创建者 Sanket K

•

Oct 13, 2020

Excellent Course Well organized

创建者 purvak p

•

Oct 9, 2020

Good content. Nice explanation.

创建者 christson h

•

Sep 24, 2020

Thank You for Such Great Course

创建者 aseel .

•

Sep 10, 2020

thanks for this valuable course

创建者 ROHIT R K

•

Aug 29, 2020

Excellent course to start with.

创建者 Paul R

•

Aug 24, 2020

Concise, but very to the point.

创建者 Ajay G

•

Jun 5, 2020

Excellent teaching methodology.

创建者 Bhaskar J D

•

May 25, 2020

Excellent Content to understand

创建者 Dr. V V R M R

•

May 7, 2020

very good inputs for TensorFlow

创建者 Edward M

•

Dec 22, 2019

Another great Andrew Ng course!

创建者 MURALITHARAN S

•

Dec 13, 2019

Nice Work, Good Learning For me

创建者 楊惇昱

•

Nov 8, 2019

Thank you. It's a great course.

创建者 Bahalul K

•

Nov 8, 2019

it is very helpful to my career

创建者 Habibur M

•

Nov 3, 2019

Easy to understand. Thank you..

创建者 Brendan F

•

Sep 2, 2019

Great explanations and examples

创建者 Harish M

•

Jun 8, 2019

Very good lectures by Andrew Ng

创建者 김화겸

•

Apr 27, 2019

Andrew ng.... i love so much...

创建者 Andrew

•

Oct 30, 2018

非常感谢coursera提供这么好的课程，内容很详实，收获很大

创建者 Bình B N

•

Sep 5, 2018

Very good tips. Clear advice :D

创建者 Xuhaoshen

•

Jul 1, 2018

Very Useful Course in Practice!

创建者 CK S (

•

Jun 17, 2018

可以很清楚地了解整個參數調整的涵義跟DL基礎理論與實務的銜接。

创建者 YixiangWang

•

Jun 17, 2018

i learnt a lot from Ng. Thanks.

创建者 yifan

•

Jun 11, 2018

Andrew is such a great teacher!