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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
63,068 ratings

About the Course

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....

Top reviews

YL

Invalid date

very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

XG

Invalid date

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

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7176 - 7200 of 7,238 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Mark L

Jul 16, 2020

great superficial intro to the content

By jerome c

Oct 14, 2018

Need more training on Tensorflow, imho

By Juan J D

Sep 11, 2017

tensorflow subject was to superficial

By Weeha G

Jul 25, 2021

Assignment of week 3 is toooo brief.

By SATHVIK S

Jul 26, 2020

Can dive deeper into the mathematics

By Trevor M

Nov 23, 2020

good lectures terrible exercises

By Maisam S W

Oct 4, 2017

I still find tensorflow hard.

By Andrey L

Oct 1, 2017

week 2 was extremely boring

By Cheran V

May 9, 2020

Outdated with Tensorflow 1

By QUINTANA-AMATE, S

Mar 11, 2018

Again, nice videos but not

By Matthew P

Sep 3, 2021

Focused a bit on minutia.

By Adam G

Jul 11, 2020

Multiple grading issues.

By Chaitanya M

Jul 1, 2020

could be more engaging

By José A G R

May 23, 2023

Estoy muy emocionada

By Cory N

Jan 8, 2020

Update for TF2.0 :)

By Алексей А

Sep 7, 2017

Looks raw yet.

By Ilkhom

Mar 21, 2019

awful sound

By Akhilesh

Mar 14, 2018

enjoyed :)

By Sai R

Nov 10, 2022

Good

By zhesihuang

Mar 3, 2019

good

By CARLOS G G

Jul 14, 2018

good

By Hoàng N L

Feb 12, 2019

N/A

By KimSangsoo

Sep 17, 2018

괜찮음

By Maximilian S

May 7, 2022

This is a nice but very basic introduction to the practice of DL (the last week about tf is nice). However, the assignments are way too shallow! In the assignments the students are "spoon-fed baby-food"... one can solve almost all exercises without thinking and without having understood anything (it is mostly solvable by copy&paste).

For instance, I have learned the most in the final assignment when it did not fully work and I forgot a tf.transpose(..) and I actually had to think about what was happening.

Anybody applying to our group who presents this course as evidence that they know about the contents will not be taken seriously (and rightfully so!) -- thanks for a very quick way to sort out useless applications (anybody presenting a certificate for this course in public).

The assignments could also be auto-graded by using the format of any programming competion (specifying the input-output relation, providing an input, and giving the student total freedom in how to implement the solution), e.g. like in the famous advent-of-code. Then the course would be harder (but way more valuable!) -- however, coursera won't get enough paying subscribers that way I assume.... oh what a pity.

By Sameer C

Oct 21, 2021

Terrible construction of programming exercises. They either end up being extremely trivial or vert obfuscated. Sometimes too much information is given with no incentive to think or too little information is given leading to a deadlock. Week 3 of this course is utterly trash. Course content feels rushed and the programming exercise does not explain anything or clear any doubts. Why on earth do I have to do so little in these programming exercises. Why can't you make us write the little helper functions and plotters and the compiled model.