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Kursteilnehmer-Bewertung und -Feedback für Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization von deeplearning.ai

4.9
39,278 Bewertungen
4,171 Bewertungen

Über den Kurs

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....

Top-Bewertungen

XG

Oct 31, 2017

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.

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.

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3976 - 4000 von 4,111 Bewertungen für Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

von Oleksandr T

Jul 29, 2019

Last code assignment is a mess. Looks like organizers have no intention to fix errors.

von Andrew W

Jul 30, 2019

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

von Harsh B K

Jul 30, 2019

Good Insights of hyper parameters with other techniques to improve learning rate.

von Aayush A

Aug 03, 2019

The Jupyter notebooks had a lot of mistakes which wasted a lot of my time otherwise the course content was good

von Shubham K J

Aug 08, 2019

Grader is not performing well even though my outputs are matching.

von Dr. H H W

Aug 08, 2019

Interesting material but a bit complex to follow all the equation derivation. Need to repeatedly watching the video to understand the content. After learning this the hyper parameter setting in the ML setup is clearer to me.

von Aditya S

Aug 09, 2019

good

von Gianluca S

Aug 10, 2019

No course material available

von Laurence G

Aug 11, 2019

Decent intro to tuning neural networks. I felt the parts on normalization and regularization could have gone into more detail, but perhaps the math was deemed too complicated. Labs are ok, but still a bit buggy despite errors being reported in the forums a while ago.

von Aymen S

Aug 13, 2019

Cours intéressant merci beaucoup Mr Andrew Ng

von Armaan

Aug 15, 2019

Extremely well designed course, the key reason for 4 stars is Andrew Ng's amazing leactures. The programming assignment though do quite a bit of handholding which can be reduced.

Amazing experience overall!

von Asad A

Aug 17, 2019

Great videos but wish there were more per-lesson exercises that were there in Course#1 for this track. Also, the transition to TensorFlow was quite abrupt as the key concepts that TF uses are completely new and don't easily borrow from the much cleaner Numpy concepts

von Mukesh K

Aug 19, 2019

The content of the Course is very precise and assignment truly reflect what is been taught in the lectures. Explanation and presentation of algorithms are what I like the most. Assignment were very engaging and interesting.

von Gerrit V

Aug 19, 2019

Sometimes quit slow

von Nguyễn H T

Aug 20, 2019

I think this course is great. Because we learn about some definitions about hyperparameters, optimization which are frequently appears in papers or in the functions in some Deep Learning frameworks.

von Elpidio E G V

Apr 23, 2019

Great explanations on behind the scenes operations of optimization algorithms and general theory. Coming from a more practical background, it helped me grasp the concepts much better. I only wish the programming exercises were a little bit more challenging!

von Surya J

Apr 23, 2019

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

von Marc D

Sep 14, 2019

The course really takes the student by the hand through the exercises. The disadvantage is that it is not really necessary to understand what you are doing. Just follow the guidance. But on the whole really satisfactory

von Khalid A

Sep 15, 2019

It is definitely very informative, but I wish the lectures would be more in depth in regards to the derivation and proofs.

von Gopal M

Sep 14, 2019

TensorFlow is a bit nebulous.I need more practice.

von Cristhian A B

Aug 28, 2019

It's a hard course but the materials are great and their explanations

von Daniel E B G

Aug 26, 2019

I think this course would benefit from a little more explaining. There are a lot of new concepts and some explanations were too quick in my opinion.

von Ralf S

Aug 28, 2019

Good course overall. but labs could be expanded. Don't know if the Coursera platform supports it, but labs between lectures about different topics would be nice instead of having all practical exercises at the end.

von Mor k

Aug 30, 2019

excellent

von Siddhi V T

Sep 19, 2019

An awesome course for someone who wants to learn how to tune the hyperparameters of their models.