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

4.9
stars
63,156 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

HD

Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.

the only thing i didn't have completely clear is the barch norm, it is so confuse

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951 - 975 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By David B

Oct 11, 2017

I would recommend these series of courses in Deep Learning to any PhD student who's domain lies somewhere else. It is a great tool to apply to your specific research topic.

By Tu L

Sep 20, 2017

Another amazing course of Professor Andrew. I have deeply understood many useful techniques to tune up DL models, which I used to adjust in a non-systematic way previously.

By Александр В З

May 16, 2021

Here was many new features for me, about DeelLearning NN training specific. Probably Tensorflow studing out of date. At least in such little volume. Better to learn Keras.

By Manuel R

Sep 12, 2020

Really great course! The way Andrew Ng teaches is so simple and yet elegant. I've learned a lot from this curse, specially some techniques to improve deep neural networks.

By tolga ş c

Sep 8, 2020

It is a wonderful course. Prof. Andrew talks all you need to understand and also implement deep learning applications. Prof. Andrew is awesome. I like this specialization.

By Michael S

Aug 23, 2020

It is a very comprehensive course on neural networks, even though the assignments are somewhat too guided for my flavor. The assignments should demand more of the student.

By Pramod H K

Jun 24, 2020

Excellent review of hyperparameter tuning and concerned theoretical background. Although introduction to tensorflow was rather brief, the experimental setup was very good.

By Robert D

Nov 9, 2019

This is an excellent course. As usual, Andrew Ng gives clear and concise explanations. The programming exercises help to explain and better understand the course material.

By Marc v W

Nov 25, 2018

As good as the first one with more insights in hyperparameters tuning and faster convergence techniques. The whole course finishes with a small introduction to TensorFlow.

By Warwick T

Mar 18, 2018

A great course which gives valuable insights about all kinds of hyperparameters, and how to treat them. Also very nice programming examples with both numpy and tensorplow.

By Alejandro A

Mar 11, 2018

After this course, I've realized that I understand much better the terminology on papers, online demos, labs, etc. But most important, that I know how the black box works.

By Tony C

Jan 4, 2021

Andrew is an amazing instructor. He explains concepts very clearly and the programming exercises are super important to make ensure we can apply the concepts in practice.

By João F

May 9, 2019

Great course covering a range of complex topics. The assignments are very good and well as the theory behind all the steps. Professor Ng is an awesome teacher! Thank you!

By Sudheer P

Jan 5, 2019

This course teaches the mechanics of deep neural networks and how to optimize the neural net. Prof goes at a reasonable pace so that the student understands the concepts.

By sh39o

Mar 12, 2018

It provides us methods of optimization and acceleration. At last, there are NN programming framework listed. The examples shown are very intuitive, which I like very much

By yassine a

Jan 20, 2018

very clear and general, I think that he covered all the aspects of regularization and hyper parameters tuning. The last videos and assignment about tensorflow was amazing

By Rajesh S

Dec 29, 2017

It was a great course which helped me to strengthen my understanding of Neural Network even more. I would like to thank Andrew N.G. and the whole team behind this course.

By Adrian S

Oct 14, 2017

In this course I learned or reviewed the following items in enough depth to perform in a job with them:

Initialization

Regularization

Batch Normalization

Optimizers

TensorFlow

By Anirudh

Jun 29, 2024

Really well developed course. If you're looking to go into the AI, this course will be very helpful. It goes into great depth on how to optimize your learning algorithm.

By Ahmad R

Oct 5, 2023

Excellent course very detailed on the theory behind the hyperparameter tuning but could be a bit more hands on with tensorflow though week had some but it was very basic

By Uttiya K

Jul 4, 2020

No doubt, this is one of the best courses on Coursera. It has got a proper amalgamation of theory and programming assignments. Special thanks to Andrew Sir and Coursera.

By Dao M D

Jun 25, 2020

Great course! It would be better if there is a summary of the workflow when one tries to solve a problem using deep neural networks with all of the techniques mentioned.

By Martin H

Dec 8, 2019

another great course by Andrew Ng, teaching us all about hyper-parameter optimization and DL frameworks. However the i did find TensorFlow 1 syntax really not inituative

By Xiaolong L

Jul 18, 2019

this is a great course teaching practical aspects about deep learning, you can learn how to implement the regularization and optimization, also learn to use tensorflow

By Subhadeep D

Feb 14, 2019

Wonderful course!!! Taught me how to tune hyperparameters and basics of tensorflow framework. Good kickstart to deep learning!! Thanks a lot Coursera and Deeplearning.ai