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Deep Neural Networks with PyTorch(으)로 돌아가기

IBM 기술 네트워크의 Deep Neural Networks with PyTorch 학습자 리뷰 및 피드백

1,289개의 평가

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


2020년 4월 29일

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!!


2020년 5월 15일

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.

필터링 기준:

Deep Neural Networks with PyTorch의 283개 리뷰 중 76~100

교육 기관: Christian T

2021년 6월 9일

Lots of errors in the questions and answers, annoying content structure, bad videos (speed, cadence, auto-generated voice that consistently mis-pronounces things). Labs that are identical to the videos. No context setting or understanding beyond trivial mechanics.

Even worse, the quizzes contain typing/syntax errors that you have to ignore and then suddenly some of the quizzes contain errors that you must not ignore.

This is a ridiculuously bad course and I have no idea how it got to getting this many good ratings.


교육 기관: Amar S

2020년 8월 22일

I am very disappointed with the quality of the course materials. The videos are recorded with what sounds like a text to speech system or a voice over done by a voice actor who does not really understand the subject matter and lacks personality.

It's hard to understand as it all runs at the same pace and there isn't sufficient time given to specific concepts that may take a shorter or a longer time to sink in depending on their complexity. It's just a constant speed monologue without any real feeling or passion in the subject matter.

교육 기관: Zaheer U R

2020년 7월 12일

Amazing course with brilliant explanation

교육 기관: Farhad A

2020년 6월 16일

It was well structured . Thank you

교육 기관: Krishna H

2020년 4월 28일


교육 기관: Pietro D

2020년 1월 3일

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

교육 기관: Ben A

2020년 8월 5일

Awful quality content that fails to teach or test you properly.

The videos are exceptionally poor using a text-to-speech narrator that makes you want to quit after only one video. Additionally, the quizzes are buggy with awful wording, typos, invisible options, and useless content. The biggest shame is that they don't use notebooks to test your learning with real examples that would reinforce both the theory & practical elements.

This course has no effort put into it & is clearly a money grab. Avoid this and instead try a or course.

교육 기관: Gopal I

2022년 4월 10일

One of the worst courses on coursera. A very complex subject is treated in an off-hand manner. Course instructions have not been updated since 2019. Labs are different from instructions. There is no lab to opne in Week 7 - I wanted the honors content.

The Watson instructions are completely outdated.

There are so many spelling errors in the quizes including misspelling simple works like "does" - looks like no one checked these materials ever.

교육 기관: Oussama B

2020년 2월 26일

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

교육 기관: A A A

2020년 7월 7일

This course is really good in explaining the concepts and pytorch. Everything was explained in a detailed way, well structured. However, I found the course too segmented. Some lectures, some quizzes, and some labs can be combined. Example for week 1, I think 1.1 (introduction to tensors), 1.2 (1d tensors) and 1.3 (2d tensors) can be combined to single lecture or all 3 lectures be one after another making it appear like it’s together. The 2 labs can be combined into a single notebook. The 2 quizzes can be combined into 1 quiz of maybe 5 or more questions. Similarly, 1.4 (Simple Datasets) and 1.5 (Datasets) can be combined, and so on. I also think that the honours content about batch normalization should be included as part of normal contents. Maybe more advanced concepts can be put up as honours contents.

교육 기관: Анатолий М

2021년 5월 9일

Курс "Deep Neural Networks with PyTorch" подходит для новичков, людей с базовым математическим аппаратом, с базовыми знаниями программирования Python и для тех, кого интересует математика нейронных сетей и машинного обучения. Курс делает упор на самостоятельность обучающихся и людей, которые сами заинтересованы в прохождении лабораторных работ. Здесь есть много инструментов для обучения, вычисления метрик, визуализации результатов, которые могут пригодится Вам в проектах. Курс прекрасно подходит для людей со средним знанием английского языка (материал разработан так, что он понятен и глазам, и ушам). Советую пройти данный курс на английском языке или с английскими субтитрами, чтобы погрузиться в изучение PyTorch и профессиональной терминологии разработчиков.

교육 기관: Erdem Ş

2020년 6월 17일

even with no mandatory peer graded assignment, for me it was the hardest course to learn in "IBM AI Engineering". So many topics and so many codes to check for each week. i liked it. i believe i will revisit the materials in the future.

교육 기관: Georgios C

2020년 8월 4일

Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.

교육 기관: Yixuan

2022년 10월 5일

Not only did I gain the basic knowledge of deep learning, but also learned Pytorch. It is a good course, however, there is still a lot more to go in the area of Deep learning,

교육 기관: Matt T

2022년 10월 16일

While there are some minor technical issues loading out of date libraries, the material and subjects are incredibly useful. This course is very difficult and welcome

교육 기관: Doğu İ

2022년 6월 10일

The explanation is simple and understandable. They explained deep neural networks so beautifully with PyTorch. Thank you very much for this course IBM.

교육 기관: Kartikey C

2020년 11월 7일

In-depth course, goes in much more detail than the usual introductory courses, also emphasizes on practical hands on rather than theoretical knowledge

교육 기관: Benjamin P

2021년 1월 19일

Good pacing, great examples and the assignments are doable within the time allocated for them. Combines both technical information and applied code.

교육 기관: Steven W

2022년 8월 5일

SO far, this has been the best designed and most informative of the four courses that I have taken so far in the IBM AI Engineering Certification.

교육 기관: Tobias B

2021년 6월 14일

Great course. Although some of the material clearly wasn't made by native english speakers, and the language usage could be improved in future.

교육 기관: Yashwardhan B

2021년 4월 20일

The course content was very well presented and was relatively easy to understand even when the pytorch framework is a bit complex. Thank you!

교육 기관: THOMONT B

2021년 1월 13일

Joseph Santarcangelo is one of the best teacher i've seen in data science.

Courses were difficult but his explanations were really clear.


2022년 10월 31일

Very detailed and well organized video lectures (quizzes not so much, just the learning material) w.r.t. fundamental understanding.

교육 기관: OMAIMA E A

2021년 5월 25일

the course was perfect goes step by step and keeps reminding the student what he studies in the sections before, I love it

교육 기관: jonathan b

2021년 11월 10일

A good introduction to deep learning with pytorch. The examples are very clear and the learning rate is not to steep