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

4.9
stars
63,295 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

AM

Oct 8, 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

XG

Oct 30, 2017

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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1601 - 1625 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Harsha V

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May 21, 2020

Nice course for beginners in Deep learning and a good introduction was provided for deep learning framework TensorFlow.

By Abderrazak C

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Apr 14, 2020

Ce cours est une étape très intéressant dans cette spécialisation. Je le conseille vivement aux apprentis. Bon lecture.

By Zeng X

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Apr 6, 2020

It really help solve a lot of question about how to improve dnn. Through this course, I learn basic knowledge about tf.

By Arpit B

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Apr 5, 2020

Initially, I thought that this course is not important for this specialization but ut turned to be an important course.

By vignesh p

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Jan 3, 2020

Well-structured course that gives you some very good insights into how hyperparameters are handled within deep learning

By Danny L

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Jan 30, 2019

great course - program assignments can be a bit harder... plus, maybe more tensorflow assignments can be really useful

By Osdel H H

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Sep 2, 2018

This course was great, I had some knowledge about the topic but I still learned a lot. Thanks Andrew and all your team.

By Raymond K

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Mar 17, 2018

Overall very good course where you quickly gain an overview of current optimization techniques for Deep Neural Networks

By AnnMargaret T

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Jan 5, 2018

Loved this installment to the specialization. Excited to explore other frameworks and applications. Highly recommended!

By Korntewin B

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Sep 11, 2017

Very good, just like the first course in this specliazation and very recommend for whom that interest in Deep Learning.

By Liekens W

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Aug 25, 2017

Great course, only remark, perhaps provide a diagram when to do what, high variance this are the options hight bias ...

By Seema N

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Apr 26, 2022

Concise and interesting course. Lectures and assignments have clarity and simplicity making this course easy to learn.

By Victoire T

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Jan 31, 2022

Concise explanation, Good intuition behind the mechanisms. Just lack a little up on the edge coding/project assignment

By Joel

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Sep 4, 2021

Great topics and very nice project at the end of week 3. As always, amazing content from DeepLearning.AI and Andrew Ng

By mohsan a

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Feb 5, 2021

the course was perfectly managed, the assignments idea and mode is amazing for intermediate learners of deep learning.

By Dharmik B

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Apr 20, 2020

this course contains all the underlying mathematical concepts of various extremely necessary deep learning algorithms.

By Gabriel C

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Mar 6, 2020

Clear and to the point. I think links to more formal research articles / Mathematical justification could be provided.

By Mahmudul H

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Feb 24, 2020

Excellent and comprehensive teaching helped a lot in learning the hyperparater tuning . and all the relevant concepts.

By Chen S

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Feb 10, 2020

loved the use of tensorflow finally it was explained with simplicity and gave me the intro i need for this framework

By Shaelander C

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Sep 13, 2019

couldn't get better! Very well explained by Professor Andrew Ng how we can increase the performance of the deep nets .

By Prashidha K

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Jul 6, 2019

Great Course. Great Instructor. I finished it in 1 week. I love that in the final assignment we get to use TensorFlow.

By Giacomo M

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May 10, 2019

Exceptional insight on how Deep model work. The part on hyperparameters is simple and exceptional. Great introduction.

By Anupam G

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Aug 19, 2018

Thanks for the wonderful course. The 'learning_rate' of the course was great. And thanks for free auditing this course

By Anirban C

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Jun 9, 2018

This was great learning, made the foundations to deep dive into the AI prog frameworks and execute real life projects.

By Mohamed F

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Sep 25, 2021

Awesome journey Thanks a lot for this course I wish we could focus some more in Tensor flow but it was good as it is