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

4.9
stars
63,175 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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1401 - 1425 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Xiang L

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Jul 10, 2018

Very nice course that provide enough information for learning start handle their optimization process and implement in their own work.

By Ramiro B O

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Mar 21, 2018

Excelent course, very useful. You will learn a lot about optimization methods and other techniques for parameter tuning. Thanks again!

By ahmed a k

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Jan 10, 2018

this course is very good it gives good practical ways to implement neural networks in python and with Tensor Flow, i like it very much

By Pham S B

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Nov 5, 2017

Another great course from Deeplearning Specialization. Strongly recommend to one who already attended the first course of this series.

By Saurabh F

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Aug 18, 2017

I loved the course 2, especially week 2, it cleared lot of doubts I had and now I have better understanding of internal details of NN.

By Daniel D H

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Aug 19, 2020

Excellent well explained tough concepts.

High quality exercises well guided to understand teorical concepts and apply in real examples

By Ihor F

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Jul 10, 2020

Very insightful course with practical tips on improving optimisation. I wish the Tensorflow notebook was updated to version 2 though.

By Oleg S

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Jun 7, 2020

The best course about hyperparameters. Now I really understand why we need regularization and how Adam optimizer works. Thanks a lot!

By Amirally A

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May 18, 2020

Best taught course in Deep Learning that i've come accross so far. Andrew explains the concepts in a way that is simple to understand

By Taiki O

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Apr 27, 2020

The code of the TensorFlow was a little bit difficult for me, but all the classes were exciting. Certainly I'll take the next course.

By Melnik A

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Apr 25, 2020

This course gives a really good inside into optimization. Neural Networks now seem lees a black box and more a beautiful math for me!

By Mo R

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Oct 23, 2019

I think it was greatly set in anyway. Exercises were good and related and enough guidance was given to move forward. Thank you Andrew

By Maulana B A

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Jul 19, 2019

This course helps me a lot to understand the concept of making deep learning more efficient and robust. Excited for the next courses!

By Ethan

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Jul 9, 2019

The content is good. The assignments are very interesting and meaningful. Helped me to learn and raised my interests in deep learning

By surya b

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May 28, 2019

Very Good course. Very well paced course due to the flexibility in deadlines. Andrew Ng's Teaching style was very easy to understand.

By Julio E H E

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May 19, 2019

This course was very helpful to learn tips of how to improve neural networks, and it also included a good introduction to TensorFlow.

By Wei-Lin C

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Aug 26, 2018

Its better to create a folder for all lecture notes! thank you. The contents are really interesting and easy to catch the concepts :)

By Sal E

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Apr 22, 2018

It was great. Lots of useful information and explained weird words.

I wish the 3rd assignment had more videos (Tensorflow how to use)

By Aral S

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Dec 14, 2017

Thanks for the very useful material. I think the lessons on Tensorflow can be presented with more details, but it is still very good.

By Atharv J

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Jul 14, 2021

This course is amazing. I learned a lot about Deep Learning models and its parameters, which helped me improve my accuracy of model.

By Juergen H

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Jul 15, 2020

Excellent course. Very good explanation of all the theory combined with many well documented program exercises for further practice.

By KARTHIK P

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Jul 11, 2020

The course gives a wide information on the various optimisation techniques available and the practice assignments are really helpful

By Severus

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Apr 23, 2020

GOOD LESSON! I've learnt hyperparameter tuning, regularization and optimization in this course, they are very useful in NN building.

By Stephen C

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Dec 16, 2019

Continue to find the structure of the lectures, quizzes, and programming assignments helpful in teaching me this subject. Great job.

By Yogesh K S

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Jun 22, 2019

An excellent course structured in a lucid manner and makes one feel neural networks is so easy. Eager to move on to the next course.