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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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3051 - 3075 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sarth S

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Feb 15, 2024

Excellent course for finer details of machine learning models

By Milad S

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Oct 29, 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 22, 2021

Great introduction to tensorflow and related tuning concepts.

By Alejandro F N

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Mar 6, 2021

Great continuation for improving my neural networks knowledge

By Saurabh S

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Feb 23, 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 23, 2020

Excellent course. Only downside is week3 is in TensorFlow 1.0

By Anil R

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Jul 3, 2020

Awesome course, Thanks Andrew ng to taught again great topics

By haiderali

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Jun 3, 2020

Simple, fact full and amazing course. Definitely recommended.

By Vishal S

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May 15, 2020

Very good course for Deep Learning revision before interviews

By Siba S P

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May 12, 2020

Yet another wonderful course by deeplearning.ai and Andrew Ng

By vikash c m

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Jan 2, 2020

Best course for Hyperparameter tuning of Deep neural network.

By Douglas C

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Dec 28, 2019

Well structured. Maybe too much help on the coding exercizes?

By Amish T

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Dec 18, 2019

Excellent course. It helps in fine tuning your neural neteork

By 曾湘

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Nov 25, 2019

nice design to clearly show the principle of neural networks.

By JackyChung

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Nov 23, 2019

Thanks for Coursera, I have learned so much from this course!

By anantharamaiah k

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Sep 19, 2019

This course gives excellent in site on Hyperparameter tuning.

By Michael Z

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Aug 19, 2019

The experiences from the teacher will help the starter a lot.

By Miguel Á S A

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Aug 13, 2019

Este curso es fantástico!!, he aprendido muchas cosas nuevas.

By Erik H

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Jul 18, 2019

Very insightful. I really enjoyed the programming assingments

By W X

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May 26, 2019

I have learned a lot from the course, and I had a lot of fun.

By Abraham K

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May 11, 2019

Loved it. All of the courses in the program are outstanding.

By Jose P

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Mar 22, 2019

This course, so far is surprisingly useful and well explained

By Graham M

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Feb 7, 2019

Very practical. Great to get to TensorFlow by the third week.