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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
별점
56,647개의 평가
6,498개의 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

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.

NA
2020년 1월 13일

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 6,427개 리뷰 중 5901~5925

교육 기관: Gleb F

2020년 11월 8일

Programming assignments are too easy, and don't help to grasp and think through the material.

교육 기관: SHRUTI S M

2020년 6월 5일

Some more details & programming exercises about batch normalization could have been provided.

교육 기관: Sanket D

2020년 6월 5일

It could be updated to include more of the newer optimizations such as Bayesian optimization.

교육 기관: Hakob J

2017년 10월 11일

It is very helpful course both for theoretical and practical aspects of Hyperparameter tuning

교육 기관: Juan A M C

2021년 1월 15일

Me llevo un tiempo, pero lo logre. Ahora a jugar con algunos datos y mejorar los resultados.

교육 기관: Manpreet S B

2018년 10월 3일

good course, easy to understand and very nicely explained concepts about the neural networks

교육 기관: Leonid M

2017년 10월 5일

It seems the major part of this course is taken from the original "Machine Learning" course.

교육 기관: Chowdepalli R R

2020년 7월 20일

tensor flow is not understood properly else the course is very good and clean to understand

교육 기관: 杨之龙

2018년 4월 4일

I have to complain why dont accompany videos with quiz and notes just like the ML coursera.

교육 기관: Hyatt B

2018년 1월 9일

Content great! I'm not convinced Jupyter notebooks are the best approach for this material.

교육 기관: Joe S

2021년 1월 6일

A good course that provides a lot of insight into how to improve upon Deep Neural Networks

교육 기관: Yen S L

2018년 8월 31일

Good explanations. But tutorials can be improved to demonstrate the various tuning effects

교육 기관: Surya J

2019년 4월 22일

Great course to build intuition about tuning NN. Solid Foundation in very short duration.

교육 기관: kritika

2019년 3월 25일

There was a lot of hand holding in programming assignments. It needs to be more rigorous.

교육 기관: Vasilis S

2018년 9월 26일

Very informative course. The assignments are too trivial. Could've been more challenging.

교육 기관: David D

2017년 10월 7일

Last programming assignments had some errors in them that could've easily been corrected.

교육 기관: Bhargava P

2020년 5월 21일

Great content. Filled with rich techniques to improve models, hyperparameter tuning etc.

교육 기관: Václav R

2019년 2월 14일

Could have focused a bit more on the tensorflow. Other than that - Great course, thanks!

교육 기관: Rajiv C

2017년 8월 25일

It was fun to get to know other optimization techniques and how to speed up the network.

교육 기관: Prajwal M H (

2020년 4월 21일

The difficulty of the course is medium. More time should be spent by learners for this

교육 기관: Andrew W

2019년 7월 29일

Felt fast faced. But a good introduction to neural network hyperparameter optimization.

교육 기관: GAURAV B

2018년 11월 13일

Course was really good, but I feel in tenserflow regularization should also be covered.

교육 기관: Ahmed A

2018년 10월 28일

The course was very informative but the tensorflow notebook was buggy and needs fixing.

교육 기관: Arjan G

2017년 12월 7일

Good course, but still has some minor issues in the assignments that needs to be fixed.

교육 기관: Nils-Jörn

2020년 12월 3일

Don't like the Jupyter environment - i loved the Octave used in the basic ML Course...