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

4.9
stars
62,820 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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401 - 425 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Yash B

Oct 22, 2019

Quite detailed curriculum. It is a great continuation for course 1 of this specialization series. As usual, Prof. Andrew Ng is there to guide our way throughout the course duration. A really fun and intriguing course which can lead to course 3 as a proper continuation.

By PeterStephenson

Jun 26, 2019

This course was perfect for me. I thought it was a good balance between theory and practice. I don't think I'm ready to start building NN's from scratch, but at least now I know how to get started. Also, I now have an understanding of the complexity of a ML project.

By Shubham G

Jun 18, 2018

Mini Batch/Adam Optimization concepts was very well explained. I was expecting the detailed derivation of the backpropagation for the batch normalization case. Overall it was a great course and it greatly improved my understanding about concepts used in deep learning.

By Favio A C

Nov 3, 2017

4.5/5 A diferencia del primer curso que es una continuacion del de Machine Learning de Andrew Ng , aqui vemos una evolución del contenido , se pasa a ver miniBatch Gradient Descent, Regularizacion , Momentum , Adam , y un inicio a tensorflow

realmente un MUY BUEN Curso

By Huaishan Z

Oct 1, 2017

Through the class, the tuning of Hyperparameter is detailed introduced and more important is that why it's tuned is very clear. Suggest persons study deep learning to study this class carefully.

Expect to have more info from the current study in University or College.

By John R

Jul 24, 2019

I guess the difficulty is what you make of it, with further studying and dedication, but I would like to encounter more challenging assignments, where one has to code entire cells for instance, as opposed to a single line here and there.

But everything else is great!

By Janzaib M

Mar 4, 2018

Contains very good understanding of Hyperparameters and their tuning process.

Secondly, teaches very well the mathematics of optimizers such as GD, SGD, GD with Momentum, GD with RMSProp and ADAM.

Finally, a small glimpse of Batch Normalization.

Highly Recommended!!!!!!

By Frank I

Aug 25, 2017

I had previously used optimizers with momentum and variance momentum (Adam) with the understanding that they helped without knowing exactly how. This course cleared up all those tiny details and has left with with a greater appreciation of neural networks in general.

By Quentin M

Aug 1, 2021

Although this particular course is not as sexy in its applications as the others it is still vital information for any serious practictioner. Prog Ng shares his years of experience and you really feel that with each video you are learning invaluable tips and tricks.

By Nguyễn V A

May 29, 2021

This is an amazing course. I've learned a lot from this course, really amazing on how to tune these hyperparameters. I think this course would be a great course that you should have if you want to become an AI engineer! Thank Coursera a lot! Everything is amazing!!!

By Igor A G d O

Sep 12, 2020

This was a great course. I could develop solid intuition about how neural networks work, and learn about state-of-the-art ways to make them better. The only thing that I have to complain about is the fact that the Tensorflow part should be updated to Tensorflow 2.0.

By Thomas N

Oct 9, 2019

This course broadened my understanding of what really happens when driving the cost function closer to its minimum and techniques to go there faster. I found this course instructive and the programming excercises helped a lot to digest the learnings from the videos.

By saikiran k

Aug 3, 2018

I know deep learning already, but I saw many people who even know it doing this specialization,so i too started like that..but its a very good experience concepts are very well explaining and I am enjoying assignments a lot it a very fun experience doing all again..

By Narek A

Oct 8, 2017

I find this course very useful, many complex ideas are presented in a very understandable way! This course is like a collection of all important aspects! However, homework could be more difficult, because now almost all the answers are given in the python notebooks.

By Sagren P

Sep 4, 2017

This specialisation is an exciting journey - can't wait to start the next course. The foundational concepts of neural networks are expertly packaged in these courses, together with enough practical exposure to get you started on a fun learning and career experience.

By MUHAMMAD A N

Nov 29, 2022

This was the second course of my deep learning specialization. So far, I have been able to get a complete grasp on how to tune the DNN hyperparameters and apply different methods like regularization effect on your parameters to further improving the Neural Network.

By Akash K

Aug 8, 2020

Best course to improve your understanding of Neural Network tuning, moreover the Tensorflow course at the end of 3rd week is really detailed, I worked earlier with tensorflow but didnt get its details accurately, but now I am confident enough about using tensorflow

By Neil S

Jun 17, 2019

Wonderful course that teaches one the intricacies of training better models. It's also great when learning to implement a neural network through Tensor Flow for the last assignment and realizing that you have a good understanding of whats going on "under the hood".

By Andrey M

Apr 9, 2020

This course is very thorough and detailed. Now I can clearly and confidently say that I can perform good research and obtain formal information and data on any topic, as opposed to just surfing the internet for genuine knowledge. Great course, well done to Andrew.

By Michael S

Aug 4, 2018

Overall, this is an excellent course, although it is not perfect. Trying to understand what is wrong when full credit is not earned for quizzes or programming assignments is sometimes "challenging". It would sometimes be useful to have more informative feedback.

By Ertu S

May 18, 2018

Great course., excellent well to the point, Only nuisance I observed is during submitting coding assingments required multiple tries since at first time, all the code somehow does not go thru. So needed to save and restart notebook and cut& pasted again. Thank you

By Белоусов А Ю

Sep 23, 2017

Great course. I really like it as it get more and more practical.

Few things might be missing from the class - it might be worth to encourage students play with algorithms a bit more. Say get back to the previous stage and add regularization to get better results.

By Christos Z

Apr 30, 2018

Grate course, only criticism is that week 3 didn't thoroughly explain how batch normalization parameters (gamma and beta) get updated during gradient descent. (i.e. how to get dgamma and dbeta). It could have been an optional lecture for the mathematically savvy)

By Siddhant A

Sep 23, 2020

One of the most comprehensive course for people who want to learn the logic, implementation and conceptual understanding for deep learning. Programming exercises are a great starting point for learning implementation and they are perfectly made for the learners.

By Abdelrahman A

May 19, 2019

it is wonderful course i learned more in Deep learning and how to apply regularization

and how to optimize cost function also programming in Tensor flow

i thanks all teaching assistant for there efforts to learn us

and i recommend this course to DL beginners