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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization(으)로 돌아가기

deeplearning.ai의 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 학습자 리뷰 및 피드백

42,297개의 평가
4,513개의 리뷰

강좌 소개

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

최상위 리뷰


Oct 31, 2017

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.


Oct 09, 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

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 4,445개 리뷰 중 4151~4175

교육 기관: Arturo V

May 29, 2019

Se podría mejorar mucho la redacción del libro del ejercicio de programación.

교육 기관: Alexander

Nov 21, 2018

more python / tensorflow, as well as data exploration and cleaning is welcome

교육 기관: Damien C

Sep 08, 2017

Excellent on the basis. could cite frameworks like hyperopt, hyperas, etc...

교육 기관: Luigi C

Aug 29, 2017

There are still some minor typos to correct, but it's a great course anyway!

교육 기관: Fredrik C

Jul 18, 2019

Great, but could be better. Fix the typos. Add summarized video notes. Etc.

교육 기관: Saurabh D

Sep 12, 2019

Insights about how machine learning works in real life is quite ingeniuos.

교육 기관: moonseok s

May 28, 2018

very good lecure.

somewhat difficult to me. I will repeat again and again.

교육 기관: John F

Jan 26, 2018

Very informative but got some issues with the last programming assignment.

교육 기관: Arjan H

Dec 08, 2017

More rigorous independent projects/assignments are needed for this course.

교육 기관: Carol Z

Aug 19, 2017

Deepened my understanding of how to make deep neural networks work better!

교육 기관: Xiaoliang L

Mar 25, 2019

Practices are more like "type after me" than a real learning opportunity.

교육 기관: Jorge G P

Oct 27, 2017

Excelent course with very interesting insigth on tuning a multilayer ANN.

교육 기관: ATIK M

Apr 25, 2019

Good can be improved by providing more code based video like Tensorflow.

교육 기관: Jaap

Jan 07, 2020

Some tricky parts in the programming assignments. otherwise great class

교육 기관: alfredo g

May 29, 2019

too math, i hope futher parts contain more implementation than calculus

교육 기관: Imran P

Oct 04, 2017

I'd like a little more focus on tensorflow, perhaps starting at week 1.

교육 기관: Pascal A S

Jul 22, 2019

A bit too technical for my taste. But useful examples to work through.

교육 기관: Rindra R

Oct 10, 2017

Good curriculum and to the point. TensorFlow introduced a little late.

교육 기관: Fabio S

Nov 04, 2019

Suggestion of references, as a complement, would be very interesting.

교육 기관: Marcos C D

Nov 03, 2019

Content needs update to leverage the state of the art in the subject.

교육 기관: Cristhian A B

Aug 28, 2019

It's a hard course but the materials are great and their explanations

교육 기관: Srivatsan R

Jun 29, 2018

Needs more real coding exercises taht aren't mainly just copy & paste

교육 기관: jian29ye4

Oct 24, 2017

generally good but hope to get more assignment about parameter tuning

교육 기관: Vishal

Mar 28, 2019

Tough Concepts are not explained clearly like dropout regularization

교육 기관: Silvério M P

Aug 31, 2018

Not as much detail on the topics as the first specialization course.