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返回到 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

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

54,263 個評分
6,194 條評論


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....



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.


Jan 14, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.


5726 - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的 5750 個評論(共 6,115 個)

創建者 Vishal

Mar 28, 2019

Tough Concepts are not explained clearly like dropout regularization

創建者 Silvério M P

Aug 31, 2018

Not as much detail on the topics as the first specialization course.

創建者 Mahendren T

Oct 30, 2017

Learnt a lot, assignments not as complex as would have hoped though.

創建者 Ali

Aug 22, 2017

Material are excellent, but some assignments have little bit issues.

創建者 Abishek V P

Aug 13, 2020

Batch norm concept isn't taught well. Otherwise the course is good.

創建者 Enyang W

Jun 05, 2019

I liked it, but the tensorflow introduction came to early I think..

創建者 Sai K S

Apr 23, 2020

There can be little more clarity in the Batch normalization topic.

創建者 Corina S

Jan 13, 2020

Informative course, last exercise could be updated to Tensorflow 2

創建者 Shubham K J

Aug 08, 2019

Grader is not performing well even though my outputs are matching.


Mar 02, 2019

Lecture were quite good. But the course assignments were too easy.

創建者 Alberto S

May 20, 2018

By itself, not really a couse. It should be part of the first one.

創建者 Muhammad W

May 12, 2018

few mistakes in course assignment but overall good course material

創建者 Michael F

Apr 20, 2018

The programming assignments were too easy, otherwise good content.

創建者 Siyu Z

Mar 19, 2018

A good course. I get familiar with the idea about hyperparameter.

創建者 Carlos P

Feb 11, 2018

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

創建者 Yide Z

Dec 13, 2017

good course but there are some small bugs in video and exercises.

創建者 Abhishek B

Aug 11, 2020

Goes bit into nity grity, which would be required in the future.

創建者 Keith H

Jun 14, 2020

Always excellent. I wish I had had Andrew as a college prfessor.

創建者 Mattia S

Mar 08, 2020

the material was good but the assignments could use improvements

創建者 Omkar K

Dec 13, 2019

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

創建者 Alexander K

Oct 12, 2019

Too less coding and practice exercises, thou the theory is great

創建者 Efthimios K

Jun 13, 2019

Good but need letter recognition NN to understand what he writes

創建者 Emanuel G

Nov 08, 2018

Tensorflow part was quite messy, but besides that, very helpful!

創建者 Yuki K

May 22, 2018


創建者 Misael D C

May 22, 2020

I had some issues regarding coding, but other than that, great!