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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
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

AA

Oct 22, 2017

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

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

筛选依据:

3101 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3125 个评论(共 7,283 个)

创建者 Fabian I M N

Mar 17, 2021

Awesome material and Andrew is one the best instructors ever

创建者 Chris P

Feb 18, 2021

Really good class. Definitely the right amount of challenge.

创建者 Emilie C

Sep 17, 2020

Great course, although we used an old version of TensorFlow.

创建者 Kabakov B

Aug 22, 2020

Great course, but please upgrade the final assignment to TF2

创建者 Rishi G

Aug 15, 2020

I finally understand how Adam optimizer works. Great course!

创建者 Alfian R

May 18, 2020

Importance notes on how to optimize the Deep Learning model.

创建者 Kalyan M

Apr 25, 2020

It helped me a lot to deeply understand the neural network

创建者 David F

Mar 25, 2020

Excellent course. Helper code still feels a little too much.

创建者 Mariola N

Feb 15, 2020

Excellent course and very useful introduction to Tensorflow.

创建者 Saurabh M

Feb 13, 2020

The course is awesome.....literally speaking... awesome...!!

创建者 Ulugbek D

Sep 7, 2019

Was very easy to follow. Straight-to-the-point instructions!

创建者 Rahul G

Jul 8, 2019

It helped me to gain deeper understanding of neural network.

创建者 Sumedh K

Jun 12, 2019

Amazing course. Put in a lot of work for this one. Loved it.

创建者 Shravan K

Jan 27, 2019

Thoroughly enjoyed this course. Thanks very much Andrew sir!

创建者 RAMON D R S

Jan 14, 2019

Un curso muy completo para introducirte a un nivel ams de DL

创建者 Vikas J (

Sep 7, 2018

It is the must taking source . Recommended. Helping me a lot

创建者 Ismael E

Aug 27, 2018

Amazing course from Andrew as usual !!! Highly recommended !

创建者 Shuangqi

May 13, 2018

Very clear course for new learners to know about the concept

创建者 Bourne

Apr 22, 2018

课程制作水准确实没的说,绝逼的超一流。最后的大作业,不知道是不是seed值不同,最后的精准度和预期不一样,但是也是100

创建者 PLN R

Jan 27, 2018

Amazing course! Looking forward to some more great learning!

创建者 David C

Dec 10, 2017

Excellent course, with an excellent teacher, I recommend it.

创建者 Rishabh A

Nov 29, 2017

Andrew Ng is awesome. He is changing the world of education.

创建者 Kadir K

Oct 12, 2017

That was a great course from Andrew Ng. Thank you very much!

创建者 Bharat J

Oct 9, 2017

Must take for all aspiring as well as current data scientist

创建者 Girish

Oct 1, 2017

Very practical and assignments give you a lot of confidence.