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Back to Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
stars
63,375 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

DD

Mar 29, 2020

I have done two courses under Andrew ng and I am grateful to 糖心vlog官网观看 for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

AM

Oct 9, 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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7201 - 7225 of 7,272 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Tadeu V (

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Jan 30, 2025

I was expecting a more hands-on practical course.

By Hasnaa T

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Feb 10, 2020

the circulum was some hard and over detailed

By luca m

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May 5, 2020

I would have loved to have a session on TF2

By Kenneth C V

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Aug 30, 2019

Course is a bit complex due to the subject

By Kartheek

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Feb 1, 2019

week 3 topics would have been a bit better

By Tushar B

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Jun 12, 2018

Assignments vs lecture, difference is huge

By Aashita G

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Jun 1, 2020

fast paced not enough emphasis on topics

By Amod J

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Mar 18, 2018

Want to download my own work but cannot.

By Rachana O

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Aug 17, 2020

Can be done in more interesting manner.

By Mark L

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Jul 17, 2020

great superficial intro to the content

By jerome c

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Oct 15, 2018

Need more training on Tensorflow, imho

By Juan J D

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Sep 11, 2017

tensorflow subject was to superficial

By Weeha G

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Jul 25, 2021

Assignment of week 3 is toooo brief.

By SATHVIK S

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Jul 27, 2020

Can dive deeper into the mathematics

By Trevor M

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Nov 24, 2020

good lectures terrible exercises

By Maisam S W

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Oct 5, 2017

I still find tensorflow hard.

By Andrey L

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Oct 2, 2017

week 2 was extremely boring

By Cheran V

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May 10, 2020

Outdated with Tensorflow 1

By QUINTANA-AMATE, S

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Mar 12, 2018

Again, nice videos but not

By Matthew P

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Sep 4, 2021

Focused a bit on minutia.

By Adam G

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Jul 12, 2020

Multiple grading issues.

By Chaitanya M

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Jul 1, 2020

could be more engaging

By Jos茅 A G R

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May 24, 2023

Estoy muy emocionada

By Cory N

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Jan 9, 2020

Update for TF2.0 :)

By 袗谢械泻褋械泄 袗

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Sep 8, 2017

Looks raw yet.