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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

42,366개의 평가
4,520개의 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.


Jan 14, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 4,457개 리뷰 중 4176~4200

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.

교육 기관: Mahendren T

Oct 30, 2017

Learnt a lot, assignments not as complex as would have hoped though.

교육 기관: Ali

Aug 22, 2017

Material are excellent, but some assignments have little bit issues.

교육 기관: Enyang W

Jun 05, 2019

I liked it, but the tensorflow introduction came to early I think..

교육 기관: Corina S

Jan 13, 2020

Informative course, last exercise could be updated to Tensorflow 2

교육 기관: Shubham K J

Aug 08, 2019

Grader is not performing well even though my outputs are matching.

교육 기관: UJJAWAL S

Mar 02, 2019

Lecture were quite good. But the course assignments were too easy.

교육 기관: Alberto S

May 20, 2018

By itself, not really a couse. It should be part of the first one.

교육 기관: Muhammad W

May 12, 2018

few mistakes in course assignment but overall good course material

교육 기관: Michael F

Apr 20, 2018

The programming assignments were too easy, otherwise good content.

교육 기관: Siyu Z

Mar 19, 2018

A good course. I get familiar with the idea about hyperparameter.

교육 기관: Carlos P

Feb 11, 2018

I would have liked to have more practice exercises about tunning.

교육 기관: Yide Z

Dec 13, 2017

good course but there are some small bugs in video and exercises.

교육 기관: Omkar K

Dec 13, 2019

Really good insight into the inner workings of a neural network.

교육 기관: Alexander K

Oct 12, 2019

Too less coding and practice exercises, thou the theory is great