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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
40,838개의 평가
4,343개의 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

CV

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 4,278개 리뷰 중 26~50

교육 기관: Felton Y

Nov 19, 2018

Incredibly useful for me!

교육 기관: Yulin C

Dec 03, 2018

It is good to cover many techniques with great details. I feel I learnt a lot from it!

교육 기관: Harkirat S A

Dec 03, 2018

Awesome

교육 기관: Srinath D

Dec 04, 2018

Another excellent course by Proffesor Ng. Lots of material to learn but neatly organized and extends the journey from the previous course. Lots of ML/DL terminology is clarified and their place and importance shown in this course. Very useful!!

교육 기관: |Anat G

Dec 03, 2018

A very good course. Andrew Ng explains things clearly and the exercises contribute to understanding

교육 기관: Rithesh S

Dec 03, 2018

Very important course for understanding hyper parameter tuning and optimization

교육 기관: Motilal R S

Dec 03, 2018

Excellent Course!

교육 기관: Amit K

Dec 04, 2018

This is good course for the student, who want to do real stuff with NN. Some of the tricks are well explained like L2,dropout, adam, momentum, minibatches etc. I think these are much needed tricks if i need to implement and tune my own NN on my own problems. I prefer to have a second level of such course which really talks about challenges in real life NN and how to solve those. Once again thanks alot for the entire Team for pulling this together.

교육 기관: Yuguang I

Dec 19, 2018

Andrew makes a mysterious subject so transparent. It is so calming to listen to his voice and understand the magic.

교육 기관: Jonathan L

Dec 18, 2018

Recommended course for understanding the importance of hyperparameters in Neural Networks and understanding the structure of the optimizers used for training (gradient descent to ADAM)

교육 기관: 陈淼博

Dec 18, 2018

NICE COURSE!It takes my a lot of time, but it indeed deserve our effort!

교육 기관: Armen D

Dec 19, 2018

This course fills many important gaps from the first course in the specialization.

교육 기관: Kavita G

Dec 20, 2018

Some of the details of the hyperparameters I wasn't aware and didnt realize the impact until I went through this course. Thank you.

교육 기관: Muhammad J K

Dec 18, 2018

Yet another amazing course

교육 기관: zhijun l

Dec 06, 2018

A great course talks about the detail in building Neural networks. With the first course as a foundation, student taking this definitely will get a better understanding on hyperparameter tuning and optimization, in addition on training neural networks. I recommend this course to those who would like to know neural networks more than just the concept!!

교육 기관: Brandon C

Dec 07, 2018

Great info, and intuition sharing

교육 기관: DOMENICO P

Dec 05, 2018

Very well organized. The right balance between theory and practice with good hands-on examples you can exercise without boring details of language syntax...

교육 기관: Hyeongseok Y

Dec 06, 2018

Best lecture.

교육 기관: Humberto d S N

Dec 07, 2018

Great explanation on Hyperparameters, Regularization and Optimization.

교육 기관: Pedro M H V

Dec 06, 2018

Great follow up course in this specialization, which introduces critical concepts to improve and design your neural network.

교육 기관: 伟杰 邓

Dec 05, 2018

I will keep taking the following courses given by professor Ng

교육 기관: Waseem

Dec 07, 2018

This course had cool insights into the workings of various optimization algorithms. It has definitely helped me go beyond the black-box understanding of Adams Optimizer / RMSProp / Momentum etc.

Highly recommended !

교육 기관: 朱荣鑫

Dec 23, 2018

As good as before

교육 기관: SW J

Dec 21, 2018

It's very much helpful. Thank you.

교육 기관: KUNIHIRO O

Dec 22, 2018

very great useful. I want to learn compute science (bachelor's degree)by top 10 of university.

that Mooc is success. I want more learning