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

4.9
stars
63,175 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

AM

Oct 8, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

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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901 - 925 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Oliver O

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Oct 16, 2017

Very good course on addressing a number of NN hyperparamater issues that I came accross when I tried to build my first ML project after the first Andrew NG course at Stanford.

By UDAY B S

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Oct 6, 2017

This course teaches you about the Hyper parameter tuning, Regularization and Optimization. This is one of the best Course which teaches core of Neural network and deep learning.

By Iain W

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Aug 16, 2017

Great course. Andrew is a great teacher. He never goes too fast, and his simpler is better method works great. Learning something difficult like machine learning was a pleasure.

By Aravindh V

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Aug 15, 2020

The discussion forum was helpful!. And hope that more exercises on tensorflow will be followed in upcoming courses. Because the introduction in the assignment was rather short.

By Grant S

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Jul 8, 2020

Good, mainly theoretical introduction to hyperparameter optimization and neural network optimization in general. Includes a guided implementation of a classifier in TensorFlow.

By Hiren V

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May 24, 2020

This course is very much helpful to have a detailed knowledge about tuning process of hyper parameters and as usual Andrew sir is best! He explains everything with so much ease

By William

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Mar 21, 2020

This is everything I am looking for. Step by step basic AI. I have already taken a couple other AI specializations but I wanted to step back and really understand the basics.

By Jae-Hong M

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Nov 2, 2018

Awesome course which gently introduces the Tensorflow module with good intuition which goes with it. A good stepping stone towards deep neural networks and their implementation

By Prateek D

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Aug 1, 2018

Andrew has taught this course to perfection, it gave me all basics to tune parameters and also th how regularization is used, how normalization helps etc.

Very awesome course...

By Tom Z

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Mar 6, 2018

This course is so good that I need to check multiple times that I get the content. Really practical when people want to try to use machine learning to solve real-world problem.

By Lorenzo P

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Jan 7, 2018

Great course, you are methodically guided through the main techniques and algorithms to make your model better. Plus, you get hands-on experience with the Tensorflow framework.

By Amit A

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Aug 30, 2017

I think Andrew has nailed engagement and clearly keeping the difficulty of the course in the "zone of proximal development" for the students.

Great course, and highly engaging.

By Md. S R

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Jul 20, 2020

Great, specifically I want to mention about the math behind the optimization algorithms. The concept is now crystal clear. Thank you so much Coursera and deeplearning.ai team.

By Vijayant Y

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Jun 22, 2020

Best place to study and increase our skills during this pandemic period. As a lot of field is using Deep Learning now, I loved this course. Thanks Coursera and DeepLearning.ai

By Ahsanul A S

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Jun 16, 2020

This course gave me very good intuitions about maintaining Hyperparameters in NN. Optimizations like ADAM were well explained. Also, it meets us with the Tensorflow framework.

By Hloniphani D

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Jul 25, 2019

The course added to my knowledge on hyperparameter tuning, especially which hyperparameter to spend more effort on when. A must do for all aspiring machine learning engineers.

By Forsaken

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Apr 13, 2018

Thanks the Coursera team provides this so outstanding curriculum! I benefit a lot and learned some brand-new and elegant optimization algorithm through the course. Thank you!

By Krishnendu D

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Feb 5, 2018

The assignments really helped me learn how to practically create models and train them better using all the techniques that can help train a model faster and more efficiently.

By Олег Д

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Oct 30, 2017

Andrew Ng does a great job explaining bias/variance in the era of Deep learning, Regularization, Optimization algorithms and other things that can speed up learning algorithm.

By Wonjin K

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Sep 26, 2017

This lecture provides experiments which helps me to understand how really deep learning work. I would recommend this course to every beginner who wants to learn deep learning.

By Jeffin S

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Sep 25, 2017

Andrew sIr teaches very well I would love to complete more courses offered by him.I would suggest him to open a course on NATURAL LANGUAGE PROCESSING and if he could take them

By Darsh K

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Jul 26, 2022

This course provides a great avenue to learn how hyperparameters work and should be tuned using various methods and practices. It also provides an introduction to TensorFlow.

By Hemshanker R

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Jan 1, 2022

Excellent Course. Detailed guidelines on how to set hyper parameters, Tuning and introduction to Tensor Flow. Perfect launch pad for next level in the worlf of Deep Learning

By Moaz M

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Nov 25, 2020

A very good course which introduced a lot of concepts in Hyperparameter tuning, Regularization and Optimization. Maybe need some programming examples for Batch Normalization.

By Koyeli M

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Aug 18, 2020

Course is awesome specially the programming assignments. I have one complain in the video subtitles should be shown in separate box as cant see end of slide due to subtitles.