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

4.9
stars
63,224 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

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.

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

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6551 - 6575 of 7,257 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Giovanni C

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Feb 11, 2019

I liked the course, but the explanation of tensorflow needs more propaedeutic introduction for a learner like me.

By Charbel J E K

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Jan 17, 2018

Really helpful ! Too much concepts to understand but only applying few in the course. I really liked this course.

By Jay R

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Dec 24, 2017

Good course to get familiar with hyperparameters and improving the neural networks. And cliff hanger was amazing!

By Mads E H

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Oct 26, 2017

Nice and practical. The assignments could go a step further in trying out different things to get better results.

By Jatin K

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May 23, 2021

Tensorflow exercise was not good , it could include some basics first. seems like only runnig it for no purpose

By Zechen Y

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Apr 12, 2020

The contents are explicit and adequate but I think It would be better if I could get more exercise about coding.

By Jayanthi A

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Apr 5, 2018

It was great course, however, I would have liked it to be a lot slower with more time being spent on Tensorflow.

By Idan H

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Feb 10, 2021

A great course!

I do feel that in order to become really good I now must apply the learned concepts myself soon.

By Johannes C d M

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May 27, 2020

Very well explained, but the Tenserflow explanation is shallow for those that have less programming experience.

By Dilip V

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Apr 29, 2020

This Course Helped me a lot in learning how to get best-optimized models by tuning Hypermeters.I really like it

By Joshua S

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Nov 13, 2019

A good course that provided more intuition on which models to work with and how to tune parameters effectively.

By Aayush A

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Aug 3, 2019

The Jupyter notebooks had a lot of mistakes which wasted a lot of my time otherwise the course content was good

By Corbin C

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May 10, 2018

Good lectures, but the jupyter notebook examples are inconsistent and sometimes use deprecated Tensorflow code.

By Srikanth C

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Oct 1, 2017

I particularly benefited from the explanations of dropout, batch normalization and the RMSProp/Adam optimisers.

By Ayesha A

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Apr 21, 2024

Many high level concepts are not explained in details so it felt quite difficult as a newbie in Deep learning.

By Arran D

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Jun 12, 2023

Despite completing the course, I feel there is much more that I could be tested on to cement my understanding.

By Narendran S

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Oct 1, 2017

TensorFlow needs more time dedicated to it. I didn't completely understand the concepts behind this framework.

By Arun J

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Sep 16, 2017

really loved the course material but would have loved it more if it gave more in depth tutorials on tensorflow

By Hector D M P

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Sep 2, 2017

Nice and clean; with nice focus in the framework; but they also could be more in depth regarding the exercises

By Crack I

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Jan 20, 2024

Great course by Andrew. The exposure and the length of what I had to learn changed the circuitry of my brain.

By Samuel C

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Sep 27, 2021

Some of the programming exercises weren't as polished as part 1 of this specialization. Still great overall!

By Shailesh

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Apr 3, 2020

Really helpful in terms of practical application and tricks/tuning for DNN. Also starts on TF which is bonus!

By Ramanjee M

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Aug 20, 2017

Quizes as part of middle of lectures help to check the understandings. For many lectures quizzes are missing.

By Pabbisetty S R

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Jul 5, 2020

explanation is very good but assignments need to be done comletely by student not like filling missing parts

By Rohit G

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Mar 26, 2020

The tensorflow portions need to be updated. Otherwise it's a great module, building on the previous courses.