Chevron Left
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

4.9
별점
60,695개의 평가
7,031개의 리뷰

강좌 소개

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....

최상위 리뷰

AB

2021년 8월 26일

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

XG

2017년 10월 30일

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.

필터링 기준:

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization의 6,977개 리뷰 중 6901~6925

교육 기관: Rishab K

2020년 4월 17일

good course to learn, but more assignments should be introduce n week3

교육 기관: Rajat K S

2020년 1월 11일

Most of the solutions to the assignment were written in instructions.

교육 기관: Ganesan G

2017년 12월 28일

I am not getting to see the programming exercises that i have done :(

교육 기관: Jonghyun K

2020년 4월 25일

voice was too small compared to noises made by clothes and others.

교육 기관: Aastha S

2021년 7월 14일

More explanations required for functions used in tensorflow lab

교육 기관: FREDERIC T

2018년 5월 13일

Good courses, the sound quality is very poor (high tone noise).

교육 기관: Suhas M

2019년 1월 20일

Interface for evaluating is not great and assignments are easy

교육 기관: Alex I E

2017년 9월 4일

The Tensorflow part should have started sooner in the course.

교육 기관: Aloys N

2019년 7월 1일

We could have more guidance on setting a tensorflow model

교육 기관: HAMM,CHRISTOPHER A

2018년 4월 30일

Lots of theory and not enough practical implementation.

교육 기관: Stefan S

2020년 9월 22일

Content starts to feel old, but still interesting.

교육 기관: Hasnaa T

2020년 2월 10일

the circulum was some hard and over detailed

교육 기관: luca m

2020년 5월 5일

I would have loved to have a session on TF2

교육 기관: Kenneth C V

2019년 8월 29일

Course is a bit complex due to the subject

교육 기관: Kartheek

2019년 2월 1일

week 3 topics would have been a bit better

교육 기관: Tushar B

2018년 6월 12일

Assignments vs lecture, difference is huge

교육 기관: Aashita G

2020년 6월 1일

fast paced not enough emphasis on topics

교육 기관: Amod J

2018년 3월 18일

Want to download my own work but cannot.

교육 기관: Rachana O

2020년 8월 17일

Can be done in more interesting manner.

교육 기관: Mark L

2020년 7월 16일

great superficial intro to the content

교육 기관: Jérôme C

2018년 10월 14일

Need more training on Tensorflow, imho

교육 기관: Juan J D

2017년 9월 11일

tensorflow subject was to superficial

교육 기관: Weeha G

2021년 7월 25일

Assignment of week 3 is toooo brief.

교육 기관: SATHVIK S

2020년 7월 26일

Can dive deeper into the mathematics

교육 기관: Trevor M

2020년 11월 23일

good lectures terrible exercises