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

4.9
stars
62,825 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

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.

JS

Apr 4, 2021

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

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326 - 350 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Hoang T H

Oct 26, 2018

I think it's a great course for those who want to learn about technics related in Neural Network and don't want to know the mathmatical underlying too much, or for those who want to get an intuition or a picture about Neural Network. Thanks Dr. Ng and Coursera a lot for giving me a great course.

By Muthu R P E

Feb 2, 2018

Very good course. We learn the basics of Machine learning and Neural Networks in the earlier course. It works fine when we work with the examples given here, but in real world, our basic program does not work. The tuning process is more important for a successful model. Thanks to Prof Andrew Ng.

By Martin S

Jun 17, 2020

Andrew Ng has a great teaching style, the lectures are always easy to follow and to the point. Weekly quizzes and programming exercises are very well done and help to reinforce the topics a lot.

The programming exercises in week 1 and 2 are very low-level and thus not relevant for real projects.

By Steven M

Mar 11, 2018

I felt like this course picked up specific problems and I was guided through them very well. Including theoretical aspects into the program assignments helped me to understand the concepts as I applied them! I also liked the funny comments every now and then. Great highly recommendable course!

By Gopikrishnan M

Dec 7, 2017

This is a beautiful course that builds on the first one, it gives all the intuitions about various hyperparameters and makes us implement all that in python. Then he when we start working with tensorflow, it all makes sense because we actually know what is going on in the functions that we use.

By Samuel Y

Oct 31, 2019

Incredible course. Very comprehensive, and goes over some awesome, industry-relevant optimization algorithms. Clear examples, programming assignments are extremely helpful, etc. Only things to improve would be to increase the difficulty of programming assignments, and focus more on Tensorflow.

By Andrei N

Sep 21, 2019

The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.

By Serkan K K

Jan 3, 2022

It has tremendously increased my intuition about hyperparameters. It made me fully grasp all the concepts. I would like to write more code in programming assignments, but if you follow the code that is already written carefully, it will be intuitive enough. Many thanks to Andrew and his team.

By Diego R

Oct 10, 2020

I really enjoyed this course. I think it is really well structured. The videos of Professor Andrew Ng are awesome and helpful (being able to explain very difficult issues in a nutshell with several examples and straightforward words!). I'm excited to go on with the rest of the specialization!

By Sanket D

May 25, 2020

The course teaches many SOTA techniques for tuning hyperparameters, various regularization techniques, various optimization algorithms. Howerver, it would have been great to get a hands-on on hyperparameters tuning in real. Rest, the course is amazing and paves a smooth way to deep learning!!

By Mohammad S I ,

Mar 26, 2020

I am really glad to learn the tuning and optimization techniques. Hopefully, I can implement them whenever I need. Learning a new framework (TensorFlow) and using it to ease up the bigger calculations was the best thing about the course. Hats off to Andrew NG for designing a course like that.

By Mahmut K

Nov 29, 2018

This second course was great in terms of showing improvements. I would have enjoyed a little more rigorous treatment of why improvements work, but then the course could go on and on... I sill think Andrew can spend a little more time on overcoming overfitting. All in all, excellent balance!

By Daniel D

Aug 19, 2018

It's a great course like the others and quite valuable. I am not quite sure how tensorflow fits into optimization, but I was glad to get a good, handholding kind of introduction to tensorflow as in these courses, I had become accustomed to doing things directly using numpy or MATLAB/Octave.

By Intan D Y

Aug 17, 2018

This course helps practitioner or beginner to know how to tune supporting parameters in order to achieve more efficient/accurate NN. In other words, this course helps me figuring how to optimize the NN design, and I think this is recommended for beginners who like to explore Deep Learning/NN

By Nachiket R A

Apr 14, 2018

This course provided a lot of insight in how to improve accuracy by tuning hyper parameters and also introduced multi-class problems and Deep learning programming frameworks! Awesome specialization to have as it aims to create well rounded expertise in Deep Learning and Neural networks area.

By Ekamjot S T

Jul 7, 2020

After the first course, This course was really important for optimizing the Deep Nets and increasing its accuracy to further heights. The discussion forum also helped in clarification of many intriguing doubts. The assignments were suffice in implementing and understanding the fundamentals.

By Малышев Я

Jun 7, 2020

Отличное продолжение первого курса от этой организации. Множество важных моментов отлично описаны, а задачи по программированию помогают закрепить это на практике. Как отдельный курс наверное не стоит наверное смотреть, но если рассматривать всю специализацию целиком - это отличный продукт!

By Vaibhav Y

Dec 12, 2019

Coursera is so amazing to provide an opportunity like this to someone who is living in a 3rd world country with almost no opportunities in a high entry barrier field like Data Science. It is inspiring to see what coursers stands for, providing a learning opportunity to everyone, everywhere.

By Sinan G

May 8, 2018

Nice breadth and depth of relevant topics in this course. Andrew Ng is as always very precise about the issues presented and helps build up our knowledge step-by-step in a super structured way. Nice to work with both Python (semi-raw) models and getting a similar introduction to TensorFlow.

By Muhammad F M

Jul 2, 2023

The way of teaching The "Andrew Ng" is just incredibel he is not just a instructor he is my mentor in th field of ML and DL or I can say tha in the field of AI envery topic he teach with very easy to understand and material was updated and easy to understand and Lab workspace was also good

By Rajeev G

May 9, 2020

Took the course to retest my knowledge in Deep learning. Have completed this course some time back. Without certificate. Professor has covered each of these topics in good detail. Practice workbooks and assignments are really helpful and provide a great start for deep learning enthusiasts.

By Xiang J

Oct 24, 2019

Really like the assignments in this course, which gives me hands-on experience with advanced knowledge such as Adam optimizer, gradient checking. Tensorflow v1 assignment is also good, but I am not sure whether API is still relevant as Keras based API for tensorflow v2 is already released.

By Tarush S

May 16, 2019

With this course, even the beginner can understand why what happens when tuning and optimizing a neural network model. With easy to understand methodology and great explanation, I highly recommend this course for anyone who wants to go deeper into deep learning and understand the workings.

By Meghdad P

Aug 5, 2018

Very helpful learning material.

I'm still a bit confused though, even after passing the exams and exercises, but I think its mostly because I've lost grasp on mathematics. So, the blame is on me not coursera.

Hopefully I would fit more in the Deep Learning world by finishing up the course ;)

By Alamath C

Feb 9, 2018

This is a great course and you get to do real programming and training of a Deep Neural network. Andrew Ng is an excellent instructor. The final assignment wasn't hard but the syntax was difficult to follow. Using the forum and the Tensorflow documentation you can make your way through.