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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:

6426 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6450 个评论(共 7,283 个)

创建者 Lian L

Nov 7, 2018

Great introduction to the tuning options for Neural Networks. Would have loved more visual representations of how different options affects learning and accuracy.

创建者 Wes H

Feb 13, 2018

Some oversights in programming assignments and the week by week content is not very balanced in terms of effort/time spent. Otherwise, I would have given 5 stars.

创建者 Julian K

Jul 20, 2018

Introduction to tensorflow was kept a bit too short for my taste and the coding part was mainly copy pasting the instruction text from above, making it too easy.

创建者 Harsh S R ( C

Apr 21, 2020

Best course explains the whole concept in detail and taught by one of the most excellent ML teachers Andrew Ng must to understand the working of Neural Networks

创建者 John S

Apr 11, 2020

Thanks for providing the coursera for me to learn more about DeepLearning!But the web sometimes cannot open the jupyter, the net work is so unstable to log in .

创建者 Keith S

Oct 2, 2017

Great course - Some small typos in the programming exercises and the Tensor video felt a bit rushed (needs 1 more video or lengthier explanations would suffice)

创建者 Thiemo M

Sep 1, 2017

A big step forward to understanding how to tune neural network performance. Didn't learn all of this even through a couple of years of trial and error on my own

创建者 ANLAN J

Dec 19, 2020

This is a very great course about the techniques of optimizing neural networks, for example, I have learned different methods to speed up the training process.

创建者 Steven K

Jun 24, 2022

- Lecture video was very educative and Andrew was a instructor

- I find the the coding assignment too easy - maybe because of the filling of the blank styling.

创建者 Carlos R V

Apr 30, 2021

The Tensor flow assignment is not clear why we don't use softwax activation at the last layer and why we use a binary cross entropy cos instead of categorical

创建者 Israël T

Jun 2, 2020

I suffered too much to handle Tensorflow since it's not well explained for beginners throughout the programming assignment. The rest of the course is awesome.

创建者 irfan s p

Feb 21, 2020

good course, but unfortunately different with network and deeplearning course, that has fast response mentor. But all in all the course is full with knowledge

创建者 Kate S

Mar 6, 2018

Excellent material! There was one error in the last assignment that cost me a lot of time. Please fix that. Otherwise, very useful programming assignments.

创建者 SUNIL D

Jul 7, 2019

Very Good Course to understand Step by Step

Hyperparameter tuning, Regularization and Optimization to improve Deep Neuaral Networks & Practical Assignments !

创建者 Hanqiu D

Aug 10, 2020

Great course and great teacher. The skills in this course is very practical. But I think the assignment should use tensorflow version 2 instead of version 1

创建者 Zach Z

Mar 26, 2020

Learned a lot about tuning and different frameworks. Definitely math-intensive and more of a brief overview than a deep dive of these techniques and tools.

创建者 Nilakshi R

Dec 14, 2019

improving Deep Neural networks :Hyperparameter tuning,Regularization and optimization course was amazing! thank you so much coursera and Andrew Ng sir! :))

创建者 Rohan P

Sep 8, 2020

Similar focus should be given on programming assignments with a extensive discussion forums. Encourage learners to find functions themselves using google.

创建者 Alex C

Sep 23, 2017

Please offer a lecture note in detail instead of just ppt shows for each class video, not to mention that some are missing which is inconvenient to recap.

创建者 Muhammad B A

Jun 25, 2018

Great material and lectures. Would've preferred slightly more comprehensive exercises though, and more on tensorflow(any deep learning framework) as well

创建者 Francois-Xavier P D

Dec 17, 2017

The tensorflow programming assignment was a little too easy. It turned out to be more or less of a copy paste work without having to look at the TF docs.

创建者 Masateru H

Jan 7, 2021

Great intro to TensorFlow Framework. But the last programming assignment was still giving low percentage accuracy without any notable fault in the code.

创建者 Behrad K H (

Jul 26, 2020

The content was perfect but last programming assignment was excruciating! But I thank everyone involved in making this course, it was unbelievably good!

创建者 Flaviu V

Apr 7, 2018

I feel like the second course was better then the first one. But there are a couple of typos in some assignments and the assignments are still too easy.

创建者 Mark M

Oct 30, 2017

The intro of hyper parameters was from mathematical point of view as good as the basics of week 1, however practical relevance becomes not really clear.