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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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3176 - 3200 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Xiaoyang G

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Nov 1, 2017

Really helpful course to learn how to tune the parameters.

By Hussein N

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Oct 29, 2017

A wonderful overview of hyper parameters and model tuning

By Venkatakrishnan B

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Oct 15, 2017

Awesome materials and way of proceeding is simply rocking.

By Ali L

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Oct 9, 2017

A must attend course. It was a great review course for me.

By Vibhutha K

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Sep 30, 2017

This is a great course to learn tuning of neural networks.

By ni_tempe

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Sep 13, 2017

very good course. The programming assignment is very good!

By Edward W

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Sep 9, 2017

Learnt a lot and coding assignment is great reference code

By Ruben P

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Mar 13, 2022

Great addition to the previous course on neural networks.

By jing h

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Oct 10, 2021

very useful contents, the assignments were well designed

By Tin T

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Jul 5, 2021

I have learned numerous techniques to optimize DL models.

By Min T K

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Dec 16, 2020

This course is really supported for me to do my research.

By Yuvaraj G

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Sep 30, 2020

Neat and through explanation of each concept beautifully

By Somnath R

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Sep 19, 2020

Really helpful when i solve real world problems using DL.

By moid h

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Aug 9, 2020

A perfect amalgamation of Theory and Practical knowledge.

By Rahat k k

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Jul 28, 2020

Well it will really help me to optimize my neural network

By JAI G

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Jun 15, 2020

As good as first course. Love to see the implementations.

By VIKAS K

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May 23, 2020

Great insight in deep NN and the best part is TensorFlow.

By Nibir H

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May 8, 2020

Really easy to understand and worthy deep learning course

By Alexis C O

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May 1, 2020

Such a great course, please, update to tensorflow 2 asap!

By Kailash C

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Apr 8, 2020

Very well designed course and easy to grasp for learners.

By Rajesh R

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Mar 21, 2020

Great courser to study and practise. Highly recommend it.

By Abhishek

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Feb 15, 2020

Amazing course, helped me with introduction to Tensorflow

By Hideyuki K

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Jan 24, 2020

Very nice course since it contains "real-world" examples.

By YIRAN W

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Nov 25, 2019

Love the last practical, great introduction to TensorFlow

By Mr.Doctor

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Oct 6, 2019

Very practicle strategies to optimize learning algorithm!