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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

4.9
40,746개의 평가
4,339개의 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

HD

Dec 06, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.\n\nthe only thing i didn't have completely clear is the barch norm, it is so confuse

AM

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 4,270개 리뷰 중 301~325

교육 기관: Yash C V

Feb 03, 2019

Awesome.

교육 기관: Chandrakant P

Feb 02, 2019

Thank you Andrew Ng

교육 기관: Navruzbek

Feb 02, 2019

very good course

교육 기관: Dana A

Feb 02, 2019

The lectures are awesome, bu think the exercise need some more polish and more depth

교육 기관: Mohammed K A K

Apr 03, 2019

Concepts such as dropout, batch norm and exponentially weight averages are explained very well with good intutiions.

교육 기관: Aman W

Apr 03, 2019

Excellent

교육 기관: Arun K M

Apr 03, 2019

The course modules were very well paced, with details as well as the programming of specific aspects of deep learning clearly explained. Thank you!

교육 기관: Saber E h

Apr 01, 2019

Thanks, Great course !

교육 기관: Kevin S C

Apr 03, 2019

A helpful tutorial if you want to understand deeply how to tune your hyperparameters. It is also good for beginners and as well as those who are refreshing their passed lessons.

교육 기관: Miguel A A U

Apr 03, 2019

Nice hints on how to improve DNN performance!

교육 기관: Dawid P

Apr 02, 2019

Alot of useful info about neural network tuning and easy introduction to Tensorflow framework. Absolutely must see for every DL novice!

교육 기관: Anad K

Apr 03, 2019

Great Course!

교육 기관: Varun P

Apr 05, 2019

Dr. Ng's courses are among the best I've seen on the web. Simple, precise, clear, easy to understand and easy to implement.

교육 기관: Augusto R

Apr 04, 2019

Thanks to this course I will now be able to improve the performance of my neural network in a more efficient way. I loved it

교육 기관: Asaduddin A Z

Apr 04, 2019

I think this section is a great tips and trick that related to deep learning. How to make your model awesome. and awesome.

교육 기관: Karel N N

Apr 05, 2019

Excellent courses, and a great teacher! Best regards and thank you very much!

교육 기관: Bin P

Apr 04, 2019

Mathematical explanation of optimization concepts.

교육 기관: 曾健

Apr 05, 2019

The teacher's explanations are in place and easy to understand. Arranged assignments are also very helpful in mastering the content of the classroom. In short, it's a very good course.

교육 기관: Paras D

Apr 06, 2019

This course is a must-do for deep learning practitioners as it teaches about the most important parts of deep learning which are essential to understand to build an efficient model.

교육 기관: Keith R

Apr 06, 2019

Great course that starts to delve deeper into neural networks. Also, there is a good introduction to using Tensorflow for neural networks that was quite useful.

Great presentations and good programming exercises.

교육 기관: Santiago G

Apr 07, 2019

Excellent! Great as I was expecting!

교육 기관: xun y

Apr 07, 2019

Again a great course about deep learning. The course structure is very well defined, with step by step to build technical foundations in the beginning and later using open source deep learning framework to connect all the pieces together. Dr. Andrew Ng made all of them very easy to learn and sometimes I feel like I should jump out the comfortable zone he created for us.

교육 기관: Ka W P N

Apr 07, 2019

The course materials are well-designed. However, I have to say this is not an easy course as I spent a lot of efforts in order to understand how to do the assignments. Overall, I strongly believe the course has taught me what I need to know about this topic!

교육 기관: Jose M M B

Apr 07, 2019

Very usefull for adquiring metodology on tunning parameters of a deep learning network

교육 기관: Wei L

Mar 31, 2019

Great