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Deep Neural Networks with PyTorch(으)로 돌아가기

IBM의 Deep Neural Networks with PyTorch 학습자 리뷰 및 피드백

4.4
278개의 평가
51개의 리뷰

강좌 소개

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...

최상위 리뷰

AN

Mar 07, 2020

It was a very informative and interesting lecture. I learn a lot about the details when using PyTorch to build and train a deep neural network. I am so thankful.

SK

Nov 17, 2019

Awesome! This course gives me the basic workflow for using machine learning technique in my research! The materials in the form of Jupyter lab really help!

필터링 기준:

Deep Neural Networks with PyTorch의 54개 리뷰 중 1~25

교육 기관: Prosenjit D

Dec 26, 2019

Horrible slides, instructor's monotonous voice, typos in exercises, and explanations are inadequate. Course is a rip off at 50 dollar a month.

교육 기관: Jordan W

Dec 17, 2019

A terrific overview of PyTorch. I was especially amazed by the lab notebooks where the author went above and beyond to plot everything in a useful way. This allowed the student to visualize everything that was going on under the hood. In each notebook, there was also multiple ways of showing how to accomplish a task whether it be coding manually or using a PyTorch function to simplify. I appreciate seeing it both ways as it really demystifies the black box of Deep Learning libraries.

교육 기관: Daniel K

Nov 20, 2019

Amazing, really informative and helps a lot !!! really liked this course and would recommend this to anyone interested in Deep learning!

교육 기관: Michael X

Jan 07, 2020

Still a decent course but compared to other courses in this series, both the content and the

presentation of the content really lack clarity.

교육 기관: Henrik S

Dec 10, 2019

While the subject of this course is interesting, the general quality of the course materials is sub-standard of what I am used to on Coursera. I posted a question on the forum that the staff never bothered to answer. I used to a much better quality from Coursera.

교육 기관: Shinhoo K

Nov 17, 2019

Awesome! This course gives me the basic workflow for using machine learning technique in my research! The materials in the form of Jupyter lab really help!

교육 기관: Pham C B

Feb 18, 2020

A good course for people who want to start with pytorch framework. This course start from sample problem to an complex ones help people understand easily.

교육 기관: Konrad A B

Feb 02, 2020

Excellent Course. The Instructor put a lot of work into the content. Thank you for sharing the knowledge

교육 기관: RuoxinLi

Dec 09, 2019

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

교육 기관: Vittorino M

Dec 09, 2019

Aprendí muchísimo. Gracias.

교육 기관: Pavan D

Nov 19, 2019

very intuitive and in depth

교육 기관: Farrukh N A

Dec 09, 2019

Best course on AI

교육 기관: ThanhTung

Dec 25, 2019

very helpful

교육 기관: Miele W

Feb 16, 2020

Well, as there are no sort of exams or real questions to answer in order to pass, it strictly depends on how much attention you put in following this course. IMHO if well studied, it gives you a solid foundation, in order to let you explore the pytorch module.

교육 기관: Eric

Jan 20, 2020

Good, thorough course. Does not hold the student to any kind of standard or accountability and quizzes are ridiculously easy to pass.

교육 기관: Pietro D

Jan 03, 2020

The course is interesting and well organized but the quiz are not challenging and full of typos.

교육 기관: Paranjape A J

Feb 13, 2020

More graded coding assignments would have been better, but content is good!

교육 기관: Konstantin S

Feb 24, 2020

Poorly prepared materials, awful quiz modules, lots of mistakes

교육 기관: Oussama B

Feb 27, 2020

Bad !!!!! Many mistakes, questions too easy !!! I am really disapointed

교육 기관: sada n

Jan 10, 2020

it is too deep

교육 기관: Yong S

Feb 03, 2020

Very well done course! The concepts are pretty clearly explained. Sometimes the labs have instructions that are a bit misleading but it's a very minor issue. I really enjoyed the instructor using colored blocks as a tool to explain codes!

교육 기관: Cristina A G

Feb 20, 2020

One of the best courses I've taken. Everything was really easy explained, step-by-step, with nice slides and lost of explanations. It is really clear and starts from the very beginning. I'll totally recommend it!

교육 기관: Mohamed E

Mar 30, 2020

this course provides a very good and cohesive introduction to Neural Networks. I learned a lot during my journey and I recommend it for anyone interesting in the field.

교육 기관: Aïssatou N

Mar 07, 2020

It was a very informative and interesting lecture. I learn a lot about the details when using PyTorch to build and train a deep neural network. I am so thankful.

교육 기관: Jeremiah J

Feb 20, 2020

It was a LONG course, very packed with info. But, I feel like I certainly learned a lot and have a great foundation for further learning.