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Вернуться к Deep Neural Networks with PyTorch

Отзывы учащихся о курсе Deep Neural Networks with PyTorch от партнера IBM

4.4
звезд
Оценки: 1,124
Рецензии: 250

О курсе

The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered. Learning Outcomes: After completing this course, learners will be able to: • explain and apply their knowledge of Deep Neural Networks and related machine learning methods • know how to use Python libraries such as PyTorch for Deep Learning applications • build Deep Neural Networks using PyTorch...

Лучшие рецензии

SY

29 апр. 2020 г.

An extremely good course for anyone starting to build deep learning models. I am very satisfied at the end of this course as i was able to code models easily using pytorch. Definitely recomended!!

RA

15 мая 2020 г.

This is not a bad course at all. One feedback, however, is making the quizzes longer, and adding difficult questions especially concept-based one in the quiz will be more rewarding and valuable.

Фильтр по:

26–50 из 251 отзывов о курсе Deep Neural Networks with PyTorch

автор: Giorgio G

4 июня 2020 г.

Great course material and explanations, so far the best of the IBM specialization.

Great job Joseph!!

автор: YEE S N

21 апр. 2020 г.

Great class! Easy to follow, teaches all important concepts for using convolutional neural network.

автор: Prasad C

22 мая 2020 г.

Not to easy , not too shallow, a perfectly comprehensive course with catholic aspects covered.

автор: Wanderson S

7 мар. 2020 г.

The course is very complete and the instructor demonstrates a lot of knowledge on the subject.

автор: Jessiedee M G

13 апр. 2020 г.

The contents are not that hard and best suited as introduction level in deep learning.

автор: Adolfo C Y

15 апр. 2020 г.

State of the art Course

I was expecting a more challenging project, 5 stars content

автор: Patrick O

31 мая 2020 г.

Excellent course! Highly recommend to anyone wanting to learn PyTorch.

автор: RuoxinLi

8 дек. 2019 г.

Very Clear explanation and rich labs. The quiz can be more challenging

автор: Mevan E

28 апр. 2020 г.

Well prepared course. I got a full overview of working with PyTorch.

автор: Alexis b

28 мар. 2020 г.

Well prepared and interesting content taught with a clear voice !

автор: Alexander M A

1 мая 2020 г.

I really enjoyed the course for its diversity and practicality

автор: Evgeniya O

4 мая 2020 г.

A very nice course with clear explanations and good examples.

автор: 석박통합김한준

6 мар. 2020 г.

Excellent lecture! I appreciate your great work! Thank you!

автор: Stefan W

26 янв. 2020 г.

Great course with in depth material & hands-on learning.

автор: Mateus N

25 апр. 2020 г.

Good introductory course! Lots of exercises and samples

автор: MUKUL K

20 мар. 2020 г.

Great course for beginners in pytorch

автор: Gordon R

30 мар. 2020 г.

Good introduction to pytorch.

автор: Pavan D

19 нояб. 2019 г.

very intuitive and in depth

автор: Samira G

30 мая 2020 г.

Outstanding course...

автор: Farrukh N A

9 дек. 2019 г.

Best course on AI

автор: Julien V

3 июня 2020 г.

Great course !

автор: Aditya G P

28 апр. 2020 г.

Awesome course

автор: ThanhTung

24 дек. 2019 г.

very helpful

автор: Dishit P

27 апр. 2020 г.

best course

автор: Branly F L

8 апр. 2020 г.

Nice..!!