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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
63,489 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

DD

Mar 28, 2020

I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

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:

7226 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 7250 个评论(共 7,283 个)

创建者 SATHVIK S

Jul 26, 2020

Can dive deeper into the mathematics

创建者 Trevor M

Nov 23, 2020

good lectures terrible exercises

创建者 Maisam S W

Oct 4, 2017

I still find tensorflow hard.

创建者 Andrey L

Oct 1, 2017

week 2 was extremely boring

创建者 Cheran V

May 9, 2020

Outdated with Tensorflow 1

创建者 QUINTANA-AMATE, S

Mar 11, 2018

Again, nice videos but not

创建者 Matthew P

Sep 3, 2021

Focused a bit on minutia.

创建者 Adam G

Jul 11, 2020

Multiple grading issues.

创建者 Chaitanya M

Jul 1, 2020

could be more engaging

创建者 José A G R

May 23, 2023

Estoy muy emocionada

创建者 Cory N

Jan 8, 2020

Update for TF2.0 :)

创建者 Алексей А

Sep 7, 2017

Looks raw yet.

创建者 Ilkhom I

Mar 21, 2019

awful sound

创建者 Akhilesh

Mar 14, 2018

enjoyed :)

创建者 Sai R

Nov 9, 2022

Good

创建者 zhesihuang

Mar 2, 2019

good

创建者 CARLOS G G

Jul 14, 2018

good

创建者 Hoàng N L

Feb 12, 2019

N/A

创建者 KimSangsoo

Sep 17, 2018

괜찮음

创建者 Dave L

Oct 3, 2024

The videos are good and go into a lot of the details. However, the programming tasks are not very useful. They basically expect you to plug certain lines into an almost complete programme, without really understanding what the individual lines - let alone the rest of the programme - really mean. Also, there is the occasional reference to lecture notes. However, those lecture notes are just the slides that are being used with hand-written annotations on top, and without the accompanying videos, they are not useful.

创建者 Fabrizio N

Dec 7, 2018

Good course content and clear exposition by Andrew. The course material however is not of a good standard. The slides can be downloaded but after all the hand scribbles by the tutor, they are barely decifrable. Some are just blank pages that need to be filled in with screenshots from of the videos. The assignements are often just a copy and paste exercise, and Jupyter crashes cause frequent loss of work.

创建者 Goda R

Feb 14, 2020

The video content is very good to get a good hang of theoretical aspects but the programming assignments are too spoon-fed because of which after doing filling the blanks, you don't feel confident enough to implement the same on your own. Instead the assignments should be changed to cases where instructions are given in words and entire function should be implemented by students.

创建者 André Ø

Nov 30, 2017

The TensorFlow part of the course felt out of place and not of the same quality as the previous material. It would have been better if another week was spent using TensorFlow to actually improving a NN and not just copy-paste an example into the assignment. Even after using TensorFlow in the assigment and passing, working with TensorFlow still

创建者 Sergey K

Jul 6, 2020

In general the course isn't deep enough. There are no summaries of the lectures, there are no excercises during lectures, the programming assignments are very weak, they don't challenge the use of lectures or anything - all necessary data are in the notebooks. All this course will be lost in a week.

创建者 Ivan I P

Apr 28, 2023

Sadly the last course assignment didn't compile properly in the sections that were outside the "graded functions" (more specifically in Week 3). Also some of the questions of the quizzes were intentionally misleading but for very unimportant details.