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

4.9
stars
63,221 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

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.

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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6626 - 6650 of 7,257 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Prasad D

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Jul 1, 2020

Some examples to be solved manually would have helped get a better understanding of the concepts

By Ayushman K

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Apr 24, 2020

Learnt a lot of new things. Only complain i have frmo this course is the use of Tensorflow 1.x .

By Digvijay R

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Jan 18, 2020

perhaps more practice of tensorflow is required. The tensorflow module also needs to be updated.

By Isaraparb L

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Jul 15, 2018

Some of the math may be hard to grasp, but the course gives a lot of useful information overall.

By Amine B

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Apr 25, 2018

Great course, very complete and instructive! The programming exercices should yet be less guided

By Shobhit K

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Aug 7, 2022

I felt Tensorflow coverage was fairly limited and more practice of Tensorflow would have helped

By Yasod S G

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Aug 3, 2020

It is better if you can provide some proper documentation for the TensorFlow coding. (syntaxes)

By mandar k

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Jul 29, 2020

Great course, learned about different hyperparameter in neural networks and their optimization.

By sathwik m

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May 9, 2020

It was a great course.

I hope we are going much "deeper" in deep learning in the next courses !

By Sebastian R C

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Mar 22, 2018

I think the material is quite basic, since it is an specialization, we could go a little deeper

By Ashish C

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Jun 25, 2021

week 3 was quiet tedious and a more explanation about tenser flow would have been more useful.

By Nabham G

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May 22, 2020

Deep learning is so Deep X'D. I got to learn so many new stuff which I wasn't aware of before.

By SHAHAPURKAR S M

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May 20, 2020

The batch normalization part needs to be more comprehensive. Else, everything is just superb !

By Dongjin K

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May 19, 2020

Hope to see the course materials and assignments get updated for tensorflow 2.0 in the future!

By Kasper J

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Oct 1, 2017

Overall a very good course. However, I was hoping for more material on programming frameworks.

By Gleb F

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Nov 8, 2020

Programming assignments are too easy, and don't help to grasp and think through the material.

By Shruti S M

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Jun 5, 2020

Some more details & programming exercises about batch normalization could have been provided.

By Sanket D

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Jun 5, 2020

It could be updated to include more of the newer optimizations such as Bayesian optimization.

By Hakob J

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Oct 11, 2017

It is very helpful course both for theoretical and practical aspects of Hyperparameter tuning

By Juan A M C

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Jan 15, 2021

Me llevo un tiempo, pero lo logre. Ahora a jugar con algunos datos y mejorar los resultados.

By manpreet s

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Oct 3, 2018

good course, easy to understand and very nicely explained concepts about the neural networks

By Leonid

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Oct 5, 2017

It seems the major part of this course is taken from the original "Machine Learning" course.

By Dhatri M

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Jun 24, 2023

The content was taught in a way that made it easy to follow, the assignments were good too.

By Mahmoud M

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Feb 10, 2022

its a great course and it delivers a lot of information in a short time and that's amazing

By Chowdepalli R R

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Jul 20, 2020

tensor flow is not understood properly else the course is very good and clean to understand