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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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2926 - 2950 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sarat C V

Sep 13, 2017

A well taught course by Andrew Ng; I would recommend it to anyone.

By YoungGun Y

Aug 28, 2017

Great balance between theory and practice. Thanks for the lecture.

By Yunfan W

Aug 19, 2017

Very practical and helpful! Thanks for providing such nice course!

By Drishti K

Sep 5, 2021

Loved the course but maybe TensorFlow needs to be explained more.

By Willibald B

Oct 23, 2020

nice course. providing some good intuition for a lot of concepts.

By LUCAS E B

Oct 6, 2020

Andrew is so clear at explaining difficult concepts. Recommended.

By swetha n

Aug 15, 2020

Thank you for the amazing teaching, Prof Andrew Ng! Learnt a lot!

By Taranpreet s

Aug 13, 2020

Andrew Ng explanations are detailed and build conceptual clarity.

By Deena Y A

Aug 8, 2020

Amazing course about Deep learning Hyperparameters. Thanks a lot.

By Deb b

Aug 6, 2020

Loved the course content and the tensorflow exercise especially !

By Nien H

Jun 14, 2020

Another outstanding course. Professor Ng is an excellent teacher!

By chhatramani s

Jun 2, 2020

amazing course, content was really helpful and easy to understand

By Hirav S

May 17, 2020

Great course. Learnt many new things about hyperparameter tuning.

By kushagra r

May 1, 2020

The assignments are great. An intro to tensor flow is appreciated

By Lukas A

Apr 29, 2020

Easy to follow and very intuitive descriptions of complex topics.

By Sreenivas M

Jan 30, 2020

Excellent second course that backs up the first course in tuning.

By SK A F

Jan 7, 2020

Nothing new to describe Andrew's course. Great lecture as always.

By Dmytro P

Oct 10, 2019

Really good improving of the skills gotten from the first course.

By Mehregan K

Oct 6, 2019

You wouldn't be able to make a good algorithm without these tips.

By Priyam S

Aug 21, 2019

as you go on further with the courses things become more clearer.

By dohyun j

Aug 18, 2019

good for hands on experience and deep understanding on algorithms

By giang t

Jun 9, 2019

The course is great. I studied a lot of knowledge in this course.

By Afonso D

Apr 9, 2019

ótimo curso para obter insights sobre implementações e intuições.

By Alex S

Oct 5, 2018

Good explanations of some essential technics for model improving.

By 景小飞

Sep 29, 2018

生动有趣,Andrew的课程将理论进行了很好的提炼,让没有基础的听众也能够对深度神经网络的改善有整体的了解。

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