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學生對 deeplearning.ai 提供的 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的評價和反饋

4.9
40,909 個評分
4,352 個審閱

課程概述

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

熱門審閱

CV

Dec 24, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.

AM

Oct 09, 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

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4176 - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的 4200 個評論(共 4,288 個)

創建者 Miaoyin W

Oct 02, 2017

Need some improvement! I think the course is a little bit rush, especially on the 3rd week. I really like the 'test' assignments, which helps me to clear out a lot of important concepts. But the programming assignments sometimes bothers me not in the way of programming, but in the way of

創建者 Asad A

Aug 17, 2019

Great videos but wish there were more per-lesson exercises that were there in Course#1 for this track. Also, the transition to TensorFlow was quite abrupt as the key concepts that TF uses are completely new and don't easily borrow from the much cleaner Numpy concepts

創建者 Ronit C

Mar 06, 2018

Thank you! :)

創建者 Narendran S

Oct 01, 2017

TensorFlow needs more time dedicated to it. I didn't completely understand the concepts behind this framework.

創建者 alex g

May 13, 2018

great course

創建者 RB

Jan 22, 2018

Good course, but the standard is not up to par compared to Course 1 and the ML course. The Week 3 Tensorflow assignment has a few mistakes and some of the code seems redundant (probably because the code was updated and the old ones were not removed), which makes it a bit hard to follow. Also the code could do better with the comments for elaboration, but nothing you can't figure out yourself using online resources. Regard

創建者 Bernardt D

Jun 26, 2018

There were some typos throughout the course.

創建者 Aakarapu S P

Jul 03, 2018

good

創建者 Venkatraman

Mar 10, 2018

Quite not challenging in the programming assignments

創建者 Carlos P

Feb 11, 2018

I would have liked to have more practice exercises about tunning.

創建者 Vasilis S

Sep 26, 2018

Very informative course. The assignments are too trivial. Could've been more challenging.

創建者 Vishnupriya V

Jun 22, 2019

As always Andrew Ng's clearly explains all the concepts along with practical programs. I would strongly recommend doing this course for a good solid understanding of neural networks.

創建者 Lian L

Nov 08, 2018

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

創建者 Gopala V

Oct 24, 2017

Definitely improved my understanding on the tuning

創建者 Isaraparb L

Jul 15, 2018

Some of the math may be hard to grasp, but the course gives a lot of useful information overall.

創建者 jyning

Dec 03, 2017

感觉作业设计的很好,可以不需要太好的编程能力就能完成,还能加深多算法的理解

創建者 Omkar K

Dec 13, 2019

Really good insight into the inner workings of a neural network.

創建者 Jeroen V

Nov 14, 2018

The graded functions could be a bit more free form, forcing you to think more about it. I sometimes feel that I'm more solving the "template", than I am thinking about neural nets.

創建者 Rekhawar N N

Dec 14, 2019

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

創建者 srinivasa a

Jan 09, 2019

its great foundational course but i feel with frameworks available the math behind it was little boring.Andrew NG is pretty good with explaining it well but sometimes felt it was too trivial

創建者 Ilkhom

Mar 21, 2019

awful sound

創建者 zhesihuang

Mar 03, 2019

good

創建者 Till R

Mar 02, 2019

Exercises are too easy, and lectures are kind of boring. The Jupyter / iPython system does not run smoothly. I ended up downloading everything on my local computer, completing the assignment there, and then pasting the code into the coursera notebook. That makes the assignments take 50% longer than necessary.

創建者 Vikash C

Jan 28, 2019

Content was good.

But the system that checks our submitted our code checks wrongly even when I wrote it correctly.

In week 2 assignment, when I submitted the code, it gave many functions as wrong coded.

I resubmitted the code after few changes, for instance a+= 2 changes to a = a+2 and string text like 'W' changes to "W". It worked fine and gave 100 points.

In short, what I observed is that the code checking system is taking a+=2 and a=a+2 as differently, also 'W' and "W" are considered different, but they are not in actual output.

創建者 Amit C

Feb 01, 2019

I wish the course mentors were more active on this course makes it a bit difficult to clear doubts