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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.


5701 - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的 5725 個評論(共 6,120 個)

創建者 Pranaydeep C

Apr 21, 2020

I really liked it because it made me specially under stable with Tensorflow

創建者 Fredrik C

Jul 18, 2019

Great, but could be better. Fix the typos. Add summarized video notes. Etc.

創建者 Shivaraj N

Aug 28, 2020

Pls update to Tensorflow 2.0. Its a bit discouraging to learn and unlearn.

創建者 Saurabh D

Sep 12, 2019

Insights about how machine learning works in real life is quite ingeniuos.

創建者 moonseok s

May 28, 2018

very good lecure.

somewhat difficult to me. I will repeat again and again.

創建者 John F

Jan 26, 2018

Very informative but got some issues with the last programming assignment.

創建者 Arjan H

Dec 08, 2017

More rigorous independent projects/assignments are needed for this course.

創建者 Carol Z

Aug 19, 2017

Deepened my understanding of how to make deep neural networks work better!

創建者 Digaamber D

Jul 18, 2020

Would have been more helpful if TensorFlow was covered in greater detail.

創建者 Xiaoliang L

Mar 25, 2019

Practices are more like "type after me" than a real learning opportunity.

創建者 Jorge G P

Oct 27, 2017

Excelent course with very interesting insigth on tuning a multilayer ANN.

創建者 Delowar S

Jun 02, 2020

this course will help me to improve my academic skill beside help future

創建者 Shahin A

Apr 18, 2020

i rate this course 4, its really good one and learned alot in the course

創建者 ATIK M

Apr 25, 2019

Good can be improved by providing more code based video like Tensorflow.

創建者 Benjamin M

Jul 24, 2020

More explanation for some of the tensorflow code could have been given.

創建者 Olena I

Apr 23, 2020

I think TensorFlow is outdated, PyTorch is the way to go in the future.

創建者 Jaap d V

Jan 07, 2020

Some tricky parts in the programming assignments. otherwise great class

創建者 alfredo g

May 29, 2019

too math, i hope futher parts contain more implementation than calculus

創建者 Imran P

Oct 04, 2017

I'd like a little more focus on tensorflow, perhaps starting at week 1.

創建者 prateek l

Mar 27, 2020

There should be more examples first of all then moving to mathematics.

創建者 Mohammad A

Feb 25, 2020

Great Explation of hyperparameter tuning and best intro to Tensorflow.

創建者 Pascal A S

Jul 22, 2019

A bit too technical for my taste. But useful examples to work through.

創建者 Rindra R

Oct 10, 2017

Good curriculum and to the point. TensorFlow introduced a little late.

創建者 Ashish G

Apr 27, 2020

course is not updates to tensorflow 2 but overall it is very helpful.

創建者 Fabio S

Nov 04, 2019

Suggestion of references, as a complement, would be very interesting.