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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

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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2876 - 2900 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Apperson H J

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Aug 15, 2019

A great deal of practical advice and methodology. Great Lectures.

By Dittaya W

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Aug 5, 2019

I got some guidelines to start tuning parameters on my own network.

By Tian Q

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Nov 15, 2018

Very helpful course for starter in machine learning and Tensorflow!

By Arjun B

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Nov 10, 2018

The best course on hyperparameters with every detail well explained

By Henry G W V

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Oct 28, 2018

Some of the numbers in the programming assignments are out of date.

By Daniel A

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Sep 19, 2018

Full of useful content and really well explained. Thank you Andrew.

By Qiuyi P

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Aug 21, 2018

Great course! Learned tons of things about how to improve ML models

By Ljubisa M

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Jul 27, 2018

Very good explanation on possible problems and how to address them.

By Rajeev S M

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Apr 24, 2018

Really helpful, especially concepts of Transfer/Multi-task learning

By Chuong N

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Mar 27, 2018

Very good tips and systematic way to tune and diagnose your network

By Adnan B

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Jan 20, 2018

Great tips as well as insights about how to training better models.

By willie “ ”

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Nov 27, 2017

Super awesome lectures and homework material. I learned sooo much.

By Krishnaprasad B

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Nov 1, 2017

As usual , great content and intuitive explanations. Thanks Dr.Ng !

By Jingyu C

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Oct 31, 2017

The housework is very helpful in understanding the lecture content.

By Harshavardhanan B V

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Oct 22, 2017

Concept explanation is very good and complex topics are dealt well.

By Tanguy d L

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Oct 4, 2017

Very good. Would have appreciated an even deeper dive in TF though.

By André H

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Oct 1, 2017

A seemingly difficult topic very good and understandable explained!

By Gaston M S R

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Sep 30, 2017

Fantastic Course as usual with Professor Andrew NG.

Congratulations!

By Min S

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Sep 5, 2017

Very good to learn tensorflow and some new optimization algorithms.

By Leonardo A

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Aug 31, 2017

Relly cool, but maybe we should implement the batchnorm (FP and BP)

By Oğuz K Ç

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Mar 14, 2023

This course give me lots of strong intuition about hyperparameters

By Amin D

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Mar 16, 2021

it was so useful with lots of practical tips and good explanations

By Moritz K

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Dec 27, 2020

Excellent course, well presented and good assignements and quizzes

By Muhammad A K

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Nov 29, 2020

The course is designed very well, tons of thanks to the professor.

By Mohammad B A

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Oct 26, 2020

I am so happy and I feel that now I am very good at deep learning