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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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3526 - 3550 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By narain p

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Nov 24, 2018

it was a very good content to start from scratch

By Ehsan G

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Oct 25, 2018

Last week was so fast, particularly tensor flow.

By Michele C

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Jul 19, 2018

useful, clear and exercises were not frustrating

By RODOLFO X B

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Apr 29, 2018

It is a great course, but you need the first one

By Arun

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Mar 6, 2018

Prof. Andrew Ng has done it again! Great course!

By 任宇凡

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Feb 28, 2018

excellent! Informative while easy to understand.

By Giulio T

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Dec 2, 2017

Great insights into the tuning of a Neaural Net!

By Rihab B A

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Nov 25, 2017

Great level of details again Andrew. Keep it up!

By Muhammed B

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Nov 11, 2017

This course is great for hyperparameter tuning .

By Jingbo L

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Oct 22, 2017

Very clear, and gives good points on the basics.

By Robin

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Sep 28, 2017

Nice course for good foundation in deep learning

By Truman P

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Sep 10, 2017

A detailed look into some really practical bits!

By Yongtao M

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Aug 25, 2017

It become more interesting than the first course

By Vishwayishwaran L

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Jul 27, 2024

nice explanations, good course explain strategy

By Ernesto R M

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Oct 8, 2023

Excelente curso, buena relacion teoria practica

By Ankit

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Apr 19, 2022

Excellent explanation of optimization concepts!

By Daniil M

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Mar 23, 2022

Great course.

Very clear and useful information.

By Janendra H D A

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Jan 4, 2021

Fantastic. Really helpful for beginners like me

By Prakhar C

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Dec 17, 2020

Great course on improving deep neural networks!

By peilang

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Sep 7, 2020

have mastered how to optimize a neural network.

By John W

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Aug 23, 2020

very helpful course for me to start learning NN

By Pinninti A

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Aug 16, 2020

Excellent flow of teaching and good assignments

By Mullangi R

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Jun 6, 2020

exceptionally good , way of teaching is awesome

By Sooraj S

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May 25, 2020

This is my first study on hyperparameter tuning

By Jayesh S

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May 18, 2020

great intuition about different hyperparameters