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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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626 - 650 of 7,216 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Pavel C

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Sep 26, 2017

I've came to this course specially to clarify hyperparameters and optimization algorithms. But decided to start from course 1 in order not to miss anything important.

I've got answers I was looking for! Thanks a lot!

By Albert M

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Feb 27, 2018

Enterteining and insightful approach to DL. I find the programming assignments very useful, hands on practice. I feel that I am capable of implementing almost from scratch a real DL NN and I cant test it performance.

By Tian Q

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Dec 26, 2018

Excellent course. Andrew balances theory and intuition perfectly when explaining a method or an algorithm. He helps me to see not only why something is mathmetically correct, but also why it makes sense intuitively.

By Waseem

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Dec 7, 2018

This course had cool insights into the workings of various optimization algorithms. It has definitely helped me go beyond the black-box understanding of Adams Optimizer / RMSProp / Momentum etc.

Highly recommended !

By Vijay A

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Dec 13, 2017

Even though setting up Neural Networks is easy, making them work according to our need requires a lot

of knowledge and practice.We get exposed to many such practices in this course.It was a great learning experience.

By Avinash K

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Nov 1, 2017

This is really good course. I have already learnt most of the topics through different books so I could complete the course very fast. Tensor flow is a very important tool and its inclusion in this course is a plus.

By Alan H

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May 11, 2020

this course does a great job explaining concepts and providing guidance in the assignments. I sometimes wish they provided less scaffolding, but my assignments in this course will be a useful resource going forward

By Mashrukh Z

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May 10, 2020

This course really helped me with some terms like L2 regularization, Dropout, Adam Optimization and finally implementing the whole idea on Tensorflow. Thanks a lot to Andrew and his associates! I loved this course.

By Asif A

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May 8, 2020

I recommend this course to all the professionals who are working in market of deep learning & machine learning. This course will equip you with all types of necessary skills to cope with real world ML/DL challenges

By Saif N

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Feb 10, 2020

This course introduces the basic and key concepts of neural networks which are essential in building deep neural networks based on their problem application. I loved how TensorFlow has been introduced with exercise

By Jonathan S

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Jan 18, 2018

Not bad, but I felt the exercises had maybe a touch too much hand holding, and he never talked about how to compute the derivatives of Adam Optimization, though of course we promptly use Tensorflow to do it for us.

By Giovani F M

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May 30, 2020

Excellent course to learn about Hyperparameter tuning, Regularization and Optimization. The concepts are well explained in an intuitive way. The programming assignments are really useful to apply what was learned.

By Debashish N

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Jun 20, 2019

I personally feel that this is one of the most important courses included in this specialization as it helps us tune our model to the best possible parameters. Don't skip this course at any cost, dear colleagues!!

By Aniruddha S H

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Mar 19, 2019

this was amazing. Explained almost all the hyperparameters, why we need those and how can we optimizat those. along with regularization, dropouts. Everything was explained from need to the hands on implementation.

By Moses W W

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Jan 2, 2018

This is an awesome Deep Learning training course, Prof Ng depict all the key and hardest part of deep learning in this one single online course, which is still a mysteries for many people without going through it.

By Omar M A

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Dec 2, 2017

The course contains lots of practical tips, and it has a wonderful and intuitive illustration of important concepts, but i think that the assignments need to be harder (not that much help provided in the notebook)

By Prakhar T

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May 20, 2021

This was a very well-structured course where the instructor explains the different parameters and hyperparameters related to building a machine learning model in quite a depth and in a very understandable manner.

By T A O

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Feb 18, 2021

Thanks again to Mr Andrew NG for this amazing course. I learned a lot about hyperparameter tuning and tensorflow. With this course, I hope I will do better in my hydrological project with deep learning. Thanks!!!

By Mindaugas M

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Feb 14, 2021

Good step by step guidance to gain initial intuition about optimization techniques and tuning! I like how it gradually builds layers of understanding of accumulated complexity by going through small pieces of it.

By Vignesh S J

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May 4, 2020

Very practical breakdown of the various optimization techniques and how one can apply them. Also this was my first exposure to Tensorflow, I felt the assignment really made it easy to get started with tensor flow

By Sandil R

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May 3, 2020

Very well explained with assignments where you can practice what you learn. The interviews with professionals were inspiring too. Learnt things that I initially thought would take me years to learn in a few days.

By Ananya R

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Jan 27, 2019

Great Course, just like the rest in the specialisation! Really like the method of teaching!! Some sections of the assignment were coded before hand but would have been nice to be able to code them as well. Thanks

By Shubham S P

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May 23, 2018

Full rating for this course, deals with the most difficult and challenging part of the deep-learning. Finding the right strategy for setting and optimizing the training. Thoroughly enjoyed, learning the concepts.

By Piyush K

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Feb 12, 2018

Concepts are presented in very crisp and clear manner. Programming assignments have been heavily commented so that learners can focus on logic and functioning of the code rather than implementation and debugging.

By Zhixun H

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Jan 27, 2018

The course materials scope, the instruction and homework are so excellent that you feel there is nearly no any obstacle for you to understand when you are leaning and practice when you just learn through homework