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

39,941개의 평가
4,252개의 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 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


Dec 24, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 4,186개 리뷰 중 76~100

교육 기관: Vivek V A

Feb 04, 2019

Course is good for a beginner goes from basics to advanced with practice assignments as well

교육 기관: Zhenwei Z

Feb 05, 2019

Very good course

교육 기관: Pedro B M

Feb 04, 2019

As always Andrew Ng is very didactic explaining different and complex hyperparameter tuning techniques and optimizations algorithms, giving intuitive explanations and examples. I've been learning a lot in these courses! And more than that, the content is presented in such a way that motivates the student to go beyond and explore/try different implementations and problems to apply. I highly recommend the course for anyone who wants to become a serious ML practitioner!

교육 기관: YuyuanLiu

Feb 04, 2019

Andrew is the best.

교육 기관: nadaradjane

Feb 05, 2019

Excellent. Need your slides, Mr Ng!!!

교육 기관: Thor T

Feb 04, 2019

Many nice hints about hyperparameter tuning

교육 기관: Akash G

Feb 05, 2019


교육 기관: Pratik D K

Feb 05, 2019

This course is a must for every deep learning enthusiast!

교육 기관: Warren W

Feb 04, 2019


교육 기관: Praneet A M

Feb 05, 2019

Great course with an excellent course structure

교육 기관: Nitin S

Jan 22, 2019

Fun, Enlightening and above all easy to understand.

교육 기관: Oukaci

Jan 23, 2019

Very very excellent !!

교육 기관: 朱柏霖

Jan 23, 2019


교육 기관: Nikesh P

Jan 23, 2019

Hyperparameters can affect our parameters and how tuning them properly would speed up our optimization is nicely taught. And it was great to know the intuition and mathematics behind other optimization algorithmswhich which was also taught very well.

교육 기관: Nagaraj R

Jan 23, 2019

Fantastic course. Took all fear away from Deep Learning.

교육 기관: Naveen D

Dec 30, 2018

Andrew Ng is the God Father of AI Teaching.

교육 기관: Christina A

Dec 30, 2018

great overview on tuning techniques with lots of examples, conveys the intuition behind the different concepts as well as its advantages and disadvantages

교육 기관: Debadatta B

Dec 31, 2018

One of the finest. Thank you Andrew Sir.

교육 기관: Beng C C

Dec 31, 2018

Great course! But I am not too sure why this should be placed in number 2, as I feel that topics such as tuning hyperparameters do not resonate well with someone who is not working professionally or is not very experienced in this field. However, still a great course as I will revisit this course when I gain more experience. I also like the last exercise on Tensorflow as there is a lack of courses on Tensorflow on the Internet, so the last assignment on Tensorflow is the most useful which I have found in the course.

교육 기관: Suraj K J

Jan 01, 2019

Andrew Ng. That's all that needs to be said. Thanks.

교육 기관: Alexandre R

Dec 29, 2018

Very well structured class as a follow-up to the first one. Heavy on information but this is a good thing. As someone who isn't pro at Python, the development part was much smoother since programming wise it is similar to the first one.

교육 기관: YIXIANG Z

Dec 31, 2018

Very good introductory material on regularization and optimization. Also introduction to tensorflow as frameworks is spot-on

교육 기관: Martin Z

Dec 30, 2018

Absolutely fantastic! :-)

교육 기관: To P H

Jan 01, 2019

Great course

교육 기관: dsp

Dec 30, 2018

Nice overview of different steps for improvement. Very accessible introduction into TensorFlow.