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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization に戻る による Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization の受講者のレビューおよびフィードバック



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....



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.


Aug 19, 2017

Yet another excellent course by Professor Ng! Really helped me gain a detailed understanding of optimization techniques such as RMSprop and Adam, as well as the inner workings of batch normalization.


Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization: 251 - 275 / 4,186 レビュー

by 江逸群

Jan 09, 2019

Thanks so much for this course

by Sijie J

Jan 10, 2019

get a lot of insight about how to improve my own neural network.

by Aditya B

Jan 12, 2019

The concepts has been explained in a fantastic way. But few suggestions:

-> After every lesson, I would love to have more pop quizes. This was the case with course 1, but I didnot get any pop quizes for this one.

-> In the quiz assignment, it would be nice to have an explanation or justification section, which will explain that why the option selected is a correct one and why the other options are incorrect. I know we can have the same discussion in the forums, but such an explanation ( one liner should be fine) can provide a good instant knowledge boost!

by Dunitt M

Jan 11, 2019

Excelente curso, aunque me quedé con las ganas de implementar la normalización de lote en Numpy antes de usar TensorFlow.

by aisibi

Jan 12, 2019


by Onur A

Jan 22, 2019

Very instructive course

by Nitin S

Jan 22, 2019

Fun, Enlightening and above all easy to understand.

by 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.

by rajesh t

Jan 22, 2019

Very interactive and very clear explanations.

by Omar R L

Jan 24, 2019

very useful and fondamental

by Nagaraj R

Jan 23, 2019

Fantastic course. Took all fear away from Deep Learning.

by 朱柏霖

Jan 23, 2019


by Oukaci

Jan 23, 2019

Very very excellent !!

by Chad W L

Jan 24, 2019

very good. maybe a bit more of a deep dive than I was expecting, but great nonetheless

by Terry P

Jan 25, 2019

Very good course and well timed with great ideas.

by Peyman G

Jan 24, 2019

this course was amazing. I really enjoyed it

by Minhao Z

Feb 09, 2019

This course is extremely helpful to real-world NN projects.

by Yingyu F

Feb 09, 2019

Tensorflow I will to use @ instead of tf.matmul but failed in grading....

by Alberto M C

Feb 08, 2019

Daunting material to go through, but massively important and well explained!

by Gregory R G J

Feb 09, 2019

Thumbs Up!

by Haris M

Jan 25, 2019

Pure Gold!

by yaomingshan

Jan 25, 2019


by Zhiliang W

Jan 25, 2019

Great lectues and exercises!

by Damianos M

Jan 25, 2019

Again, a very structured course with Dr. Andrew Ng being so calm and simple explaining all methods of the course. It was worth my time! Many thanks to the organizers :)

by zhengli

Feb 06, 2019

thank you very much!