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Отзывы учащихся о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization от партнера

Оценки: 60,677
Рецензии: 7,028

О курсе

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....

Лучшие рецензии


13 янв. 2020 г.

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.


18 апр. 2020 г.

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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351–375 из 6,976 отзывов о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

автор: Sanjay R B

16 июня 2019 г.

Very helpful in building on the foundation in neural networks and deep learning with practical experience. The programming assignments are reinforce key concepts and are a great asset to keep after the class and apply in projects. Andrew is doing great work bringing AI to the masses!

автор: Dustin

4 мая 2019 г.

Nice illustration of the tricks including Batch-Norm, Optimization as well as Dropout, etc. Sometimes the lack of the theory is sort of unstatisfying, but considering the difficulty of a comprehensive intro for all of the above, it has been good enough for beginners to catch up with.

автор: A S M A M

1 янв. 2018 г.

While the first course in the specialization is the perfect introduction to the realm of NN, this course is the place where I learned to implement a true Deep Network. It talks about various optimizations and parameters of the DL models. Bonus, it introduces the tensorflow framework.

автор: Ananth K

24 окт. 2017 г.

Great course! Very well laid out approach to tuning a deep neural network. FInal introduction to Tensorflow was useful, but I think a lot of information was compressed into a single video. Suggest spreading this a little more. The Tensorflow programming assignment was pretty good.

автор: Alberto B

7 окт. 2017 г.

Genial curso en el que aprender como optimizar tu red modificando una serie de parámetros y usando diferentes algoritmos. Ademas genial introducción a Tensorflow con el que avanzar en el montaje de redes de manera rápida. Recomendado totalmente tras realizar el curso anterior a este.

автор: Anurag A

10 сент. 2017 г.

This course is awesome. I never had this deep understanding of tuning hyperparameters, batch normalization and regularization before taking this course, though I went through several online material. The Tensorflow introduction and subsequent programming assignment is also excellent.

автор: The M G

10 янв. 2020 г.

The best course ever. I am highly impressed with the way Andrew Sir teaches and the depth of the topic, that he explains. You will never be left with a question unanswered. I am grateful to you sir, it made my life. Looking forward to complete the rest of the specialization courses.

автор: Taras M

26 июля 2018 г.

It would be super cool if this course could be extended with pytorch just to compare with tensorflow. Usually courses are extended on udemy, for instance (not a marketing, just a comparison), even after all the materials are completed. It would be sand to have this course abandoned.

автор: Sreevishnu D

19 окт. 2020 г.

Second course of the specialization and I absolutely love the content and teaching methodology. As always got an elaborate and intuitive understanding of the topics with the best advise and practices on Improving Deep Neural Networks.

Thanks Andrew Ng, and Coursera.

автор: Kalinchuk I A

7 мая 2020 г.

Thank you, Andrew and the others, who helped him! The tests are very useful and lectures give enough theory to understand everything. The only think I would like to add is a quiz. Quizzes are very useful and can be used so as to make your brain repeat the what you heard in a video.

автор: M A

21 мар. 2020 г.

As a 2-3yrs experienced deep learning developer should say that this specialization is awesome specifically this course, it's really practical every day to get a better result just tune the parameters as you've learned in the course and boom that's it you get a better model. Thanks

автор: GAURI M

30 мая 2020 г.

It is amazing how concepts can be made so clear that implementing them by hand seems so easy. Love how the instructions are commented in the programming assignment. It helps you complete the assignment easily, yet giving such an extreme feeling of fulfilment and accomplishment. :)

автор: Nektarios K

7 янв. 2018 г.

Really loved this course! I believe it is really important for anyone who completed the first one to enroll on this one as well as it goes over many important topics that are critical in implementing Neural Networks. And finally, it goes over Tensorflow which was really fun to do!

автор: Emilio D P

24 сент. 2017 г.

Fantastic course on Deep Learning. The concepts explained during the course are very useful, especially regularization (week 1) and optimization (week 2). The introduction to TensorFlow is great. This course has allowed me to read technical articles about DNN and understand them.

автор: Saurabh R

2 сент. 2020 г.

The discipline with which the code examples are put can make anybody learn Deep Learning with no prio Experience.I have thoroughly enjoyed each and every assignment and tutorials and I am amazed with the way Andrew NG has put the lectures. Kudos to the team behind this course !!

автор: Timothy G

15 июля 2019 г.

This course was very helpful learn so additional information on hyperparameters which help me out at work. Where I was tuning my own and was able to get 88%. After taking this course and implementing what I learned into auto tune my hyperparameters my accuracy went up to 91.33%.

автор: tlinden

30 мая 2018 г.

This lectures + programming examples are very good for a kick start and to understand key concepts. I'm a mathematician, diving into deep learning. I really appreciate this course. The programming examples are valuable even if my python knowledge is on a beginners level. Thanks!

автор: Dipanjan G

3 февр. 2020 г.

This again is an excellent insight on the hyper parameters and deep learning frameworks. The extreme prowess in the subject but at the same time a very lucid and relaxed style of teaching from Andrew helps quickly grasp these difficult concepts. Looking forward to much more!!!

автор: RAGHAV S

25 мая 2018 г.

This is such a crucial course to build upon the fundamentals of Neural Networks.

Especially the intuitions that Andrew has provided really add to the arsenal, I'm so glad I took this course.

Looking forward to the other courses in this specialisation.

Thank you Andrew/Coursera :)

автор: Erik E

1 окт. 2017 г.

This is a great course!! In this course a lot of the previous concepts start to be refined and streamlined for efficient implementation. I feel like this course gave me a better handle on the concepts that have been building since my first Machine Learning course by Andrew Ng.

автор: Dishant G

28 сент. 2019 г.

Very well explained each and every concept only I had struggle in gradient checking and every other video and quizzes are great. I hope after doing these courses I will definitely get a good career start after my graduation.

Andrew Ng Sir is Greatest teacher I have found yet.

автор: Miguel P d L

26 нояб. 2017 г.

Excellent course, even using intuitions Prof. Andrew Ng is able to communicate the very details of the different regularization approaches, as well how to do a good hyper-parameter search. Finally it introduces the TensorFlow framework with a very nice programming assignment.

автор: Xinghao Y

4 авг. 2020 г.

The most exciting part of this course is the exercise in the last week. The Python/Numpy code structure for a neural network learned in the previous course can be directly translated into the TensorFlow structure intuitively, which makes it easier to learn and to understand.

автор: Japesh M

10 июня 2020 г.

The Deep Learning course is in great flow and can't get any better than this. I highly recommend specialization on Coursera for all the aspiring Deep Learning practitioners. Trust me you'll learn everything, right from the fundamentals to the advanced topics.

автор: Yang Z

15 дек. 2019 г.

This course gives learner a high level strategy in tuning hyperprameter. It teaches me not only the knowledge but also the intuition about the processes. It is also great to learn how to use Tensorflow framework in training models. Great job team and Andrew!!