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6,579 Bewertungen

Über den Kurs

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top-Bewertungen

NA
13. Jan. 2020

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.

AM
8. Okt. 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

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226 - 250 von 6,500 Bewertungen für Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

von Tanveer M

27. Aug. 2019

Professor Ng's very clearly put a lot of thought into breaking down deep learning into the most understandable way for students around the world and it shows through the quality of this course. I cannot recommend this course enough to anybody who is looking to do machine learning, or simply understand the process from a high level.

von Murali T

14. Jan. 2021

As usual Andrew ng Course is Awesome.

A bit of more video expatiation is needed for Tensorflow.

Labs are really helpful.

It would be grateful if they had provided notes after each lesson like in the first course(probably 1st I guess) of Andrew ng Machine Learning .

That's it, overall it is really good and useful .Thank you Andrew Sir

von Satvik C

10. Sep. 2020

Andrew NG is such a fantastic teacher especially in this online mode. He provides crystal clear explanations and examples to understand why the methods work. As a learner I was only expecting to learn how to apply this to solve real problems and not to learn theoretical subtities, this is probably the best course in deep learning.

von Hari G S

13. Mai 2020

Excellent course over all, but what I like the most is how the complex math behind all these techniques are carefully hid and instead, we're given an intuition about how these techniques work. Of course, for a deeper understanding much more mathematics is needed, but they make sure that everyone has an idea about why things work.

von Bernard O

23. Okt. 2018

The tips and great guidelines one gets from this course are gems in their own right. Practitioners in particular will get to appreciate all the usable advice to improve their neural networks and at the same time get to understand the principles behind the scenes on what truly drives those optimizations. Highly recommended course.

von Sinkovics K

15. Aug. 2018

The course material is detailed and comprehensive and presented in a very digestible way. I felt like the home works lack a few topics (e.g. learning rate decay implementation, which I would find to be a useful exercise), but they give you a good understanding of what is going on. All in all, I definitely recommend this course!

von Dinesh T

16. Feb. 2021

Improving DL Networks in fact improved my understanding of hyperparameter tuning, regularization and optimization. The quizzes helped me getting clarity and the assignment of tensor flow gave a good introduction using functions in the tensor flow. I really enjoy learning from Andrew and look forward deep diving farther into DL.

von jxtxzzw

16. März 2020

After learning the basic knowledge of the first course, this course deepened my understanding of deep learning, and explained how to optimize the model of deep learning from the perspectives of hyperparameter tuning, regularization and normalization, and finally provided the basic knowledge of the framework based on TensorFlow.

von Kazi M R

6. Juni 2018

From this course I have learnt several important hyper parameters, regularisation and optimization of deep neural network. Most importantly I got my first hand-on experience on Tensorflow framework by which creating deep net modes are quite easy if someone knows the elements of a deep net. I wish I will proceed for next course.

von Ian C

1. Okt. 2017

Learning about TensorFlow is brilliant. It's very hard to get a good understanding of what goes on in TensorFlow without fully understanding the neural network coding setup. This course beautifully combines the two. There were some minor frustrations with the final TensorFlow programming exercise, but overall this is excellent.

von Pawan S S

8. Jan. 2021

One of the rare courses teaching about structured hyperparameter tuning. All the subject matter are well taught and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials. I highly recommend this course for any deep learning enthusiast.

von Jeroen M

10. Jan. 2018

Great course, a few rough edges in the exercises and I also feel the exercise comments give away a bit too much (would be better if the student needed to figure out things by himself a little more). But these are minor details, I've learned a great deal in an amazingly short span of time, from one of the top minds in AI today!

von Jeff R

1. Okt. 2017

I appreciate the large amount of time that has gone into preparing this course. I note that there are a large number of corrections in the errata forum that have not been reviewed by staff. In particular there are some obvious errors in the programming assignments that could easily be corrected with a small investment in time.

von Pranshu A

22. Aug. 2020

Awesome, Amazing, Best, Fabulous course. Learnt a lot about Hyperparameter tuning and atlast got an intro about tensorflow framework which i wanted to start learning but earlier afraid from it's complexity which is explained so good in this course. Best course for Tensorflow Intro and Hyperparameter tuning in Neural Networks.

von Murat T

23. Dez. 2018

Topics cut in to sections are well defined and so clear. Programming assignments definitely gives you hands on experience. Also, math is demystified that you track with high school math. If you used framework like Keras and you want to know why and when you need to use that function,parameter etc., you would love this course.

von Gilles D

5. Sep. 2017

Eventually a clear and definitive explanation about Network initialization, regularization and optimization. Good insight share on hyper-parameters prioritization.

We learn the how and why and suddenly, it all becomes a little bit less mysterious. It is all clearly explained in a very accessible way.

Great value for my needs

von Xuefeng P

29. Aug. 2017

This course really gives you a fundamental and practical ideas about the hyper-parameters of DNN, and the way of tuning them. The part I liked most is the last programming assignment ---- play with Tensorflow!!! The assignment walks you through Tensorflow structure and basics in a very organized fashion.

Highly recommended!

von Ali n

7. Juli 2020

Best course for learning Hyper parameter tuning, Regularization and Optimization topics further more the batch and other various optimization algos like momentum, Adam, Batch norm etc are much easier here. Please have a look on ground reality too, Take quiz before staring any course that this candidate is suitable or not

von Mihai L

21. Jan. 2018

This course is also interesting. The art of tuning hyper parameters and other optimization techniques are very interesting and nicely explained.

The introduction to Tensorflow and assignment is also interesting.Overall the difficulty is not high but the concepts are really powerful and important ,most scaffollding is done

von Vlad M

7. Sep. 2018

The course part is overall good.

The last assignment can be improved in two key ways:

The comment # Z3 = np.dot(W3,Z2) + b3 should be # Z3 = np.dot(W3,A2) + b3 - figured this out by myself without help from forums. :)

Also, the Adam optimization is not very apparent in the instructions - searched in the forums for issues.

von Evandro R d P J

22. Okt. 2020

Another wonderful course of this amazing specialization. I could say a lot of things, maybe even pages on how Professor Andrew it's the right person to teach you about Deep Learning but I'll shorten in this review and recommend the whole specialization for you! It's worthy and there's a lot of knowledge to be shared!

von Brad M

22. Aug. 2019

In my deep learning classes in academia, hyperparameter tuning was always "hand-waved" away - my questions were always deflected, or put off. This class answered every one of my questions, and made me more confident I'd be able to implement a DL system in industry, and be satisfied with the results. Very good course!

von Zeinab B

4. Mai 2020

This course will cover everything you need regarding your neural network performance. I always had questions on why and when you use Adam, SGD, etc. and after this course, I have a much better understanding of how to choose hyperparameters and optimization methods. I highly recommend this course to ML practitioners.

von Toby K

1. Nov. 2019

I am working through the DL specialisation. Consistently good teaching style and the programming assignments are suitably pitched for getting the learner to pick up methods quickly e.g. Tensorflow syntax for self-application later. Good course and looking forward to the next in the series. Well done Andrew and team.

von Ankur T

21. Nov. 2018

word is not sufficient signup and experience it. For a deep learning beginner who already have math background can easily understand concept behind it but for implementation you need to refer extra materials on internet and book too. Andrew Ng explain only concept and recipe but for practice you will struggle hard.