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

4.9
stars
63,068 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

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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.

YL

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very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

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3076 - 3100 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By poleNgrek

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Dec 9, 2018

A great course, suitable for everyone and easy to comprehend!

By Sidharth S

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Oct 22, 2018

Learned so much about deep learning optimisation. Amazing !!!

By Nwatu T J

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Mar 31, 2018

Concepts were presented with an intuitive approach. Awesome !

By Kurt S

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Mar 4, 2018

Good introduction and content for Optimizing Neural Networks.

By siddartha y

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Jan 22, 2018

Very fast. Would not recommend to non maths background people

By Kirsten S

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Nov 5, 2017

another amazing class. I really like the whole series so far.

By Muhammad A b C M

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Sep 15, 2017

Very good, such a new perspective obtained after this course.

By Gerzson D B

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Sep 4, 2017

Fantastic course, useful details, understandable explanation.

By Olorato M

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Aug 17, 2017

This is awesome but there are some confusing debugging issues

By Oliver O

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Aug 12, 2023

excellent course, the information is very clear and detailed

By Fabian I M N

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Mar 17, 2021

Awesome material and Andrew is one the best instructors ever

By Chris P

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Feb 18, 2021

Really good class. Definitely the right amount of challenge.

By Emilie C

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Sep 18, 2020

Great course, although we used an old version of TensorFlow.

By Kabakov B

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Aug 22, 2020

Great course, but please upgrade the final assignment to TF2

By Rishi G

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Aug 16, 2020

I finally understand how Adam optimizer works. Great course!

By Alfian R

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May 18, 2020

Importance notes on how to optimize the Deep Learning model.

By Kalyan M

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Apr 25, 2020

It helped me a lot to deeply understand the neural network

By David F

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Mar 25, 2020

Excellent course. Helper code still feels a little too much.

By Mariola N

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Feb 15, 2020

Excellent course and very useful introduction to Tensorflow.

By Saurabh M

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Feb 13, 2020

The course is awesome.....literally speaking... awesome...!!

By Ulugbek D

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Sep 7, 2019

Was very easy to follow. Straight-to-the-point instructions!

By Rahul G

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Jul 8, 2019

It helped me to gain deeper understanding of neural network.

By Sumedh K

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Jun 12, 2019

Amazing course. Put in a lot of work for this one. Loved it.

By Shravan K

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Jan 27, 2019

Thoroughly enjoyed this course. Thanks very much Andrew sir!

By RAMON D R S

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Jan 15, 2019

Un curso muy completo para introducirte a un nivel ams de DL