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

4.9
stars
63,510 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

RR

Jun 13, 2020

Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

DH

Apr 27, 2020

Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.

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3051 - 3075 of 7,287 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By jackytu256

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Mar 11, 2019

great course to deeply understand the meaning of Deep learning

By Vital

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Mar 4, 2019

Easy, thanks for good suggestions and interesting information.

By Md. M H

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Feb 13, 2019

Great course and great tutorials on a deep learning framework.

By 伟杰 邓

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Dec 6, 2018

I will keep taking the following courses given by professor Ng

By Vinay M

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Aug 15, 2018

Excellent start for using TensorFlow and hyperparameter tuning

By Sudip C M

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Aug 6, 2018

Excellent introduction to hyperparameter tuning and tensorflow

By Shounak D

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Jul 31, 2018

Great course as usual..excited to complete the specialisation.

By SUBHABRATA T

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Jul 23, 2018

In depth theory but i need some more programming explaintion .

By rachit g

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Jul 18, 2018

Excellent course. This course has no substitute in the market.

By Ganesh R

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Jun 30, 2018

Good course to understand the Hyperparameters and Optimization

By Divya R

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Mar 31, 2018

Great, but gets complex. Which is good, but also difficult! :)

By Cheryl A

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Mar 22, 2018

Really great insights and intuition on tuning and optimization

By Phi N V

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Dec 15, 2017

the course is so good but the problem set should be more handy

By Amit P

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Dec 8, 2017

Anyone who wants to learn Deep learning must take this course.

By Rodney R

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Nov 16, 2017

Amazing course! That explain step by step how to do.

Thank you.

By Amy L

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Oct 24, 2017

Amazing Course, the teaching approach is from shallow to deep.

By Khurram S

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Oct 13, 2017

Great course! good to learn Hyper Parameter to tune Parameter.

By Sarth S

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Feb 16, 2024

Excellent course for finer details of machine learning models

By Milad S

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Oct 30, 2021

this is LOVELY course, TNX you mr NG and coursera.

with LOVE

By Shahnawaz S

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Sep 14, 2021

I like the content and the way trainer explained all about it

By Hengrui C

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Jul 23, 2021

Great introduction to tensorflow and related tuning concepts.

By Alejandro F N

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Mar 7, 2021

Great continuation for improving my neural networks knowledge

By Saurabh S

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Feb 24, 2021

Very much enjoyed doing this course. Cheers, Andrew and team.

By Apurva T

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Nov 28, 2020

Perfect course to learn Hyper-parameter tuning and Tensorflow

By Rafael M

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Jul 24, 2020

Excellent course. Only downside is week3 is in TensorFlow 1.0