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Avis et commentaires pour d'étudiants pour Deep Neural Networks with PyTorch par IBM

4.4
étoiles
728 évaluations
160 avis

À propos du cours

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...

Meilleurs avis

SY

Apr 30, 2020

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

May 16, 2020

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.

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126 - 150 sur 161 Avis pour Deep Neural Networks with PyTorch

par Mohd N K

May 14, 2020

very practical

par Richard B

May 17, 2020

Challenging

par Michael H

Jun 21, 2020

This course was not to the same standard as some others I've taken on Coursera. I think the concepts would have been very hard to follow if I hadn't already taken the Deep Learning specialization, so it isn't a great conceptual introduction to Deep Learning. That said, it also doesn't deeply explore the nuances of the PyTorch library, or give very much guidance on best practices or how it differs from other popular frameworks like Keras/TensorFlow. The quiz questions are fairly shallow (and often frustratingly ambiguous). Probably the best part of the class are the ungraded lab assignments.

par Simon P

Oct 17, 2020

The awful text-to-speech voice in the videos and the "We do this.... we do this... we do this..." information dump is poor from a didactic point of view.

The redeeming feature of the course are the labs, but like many of these little courses there's little encouragement to play around with the code.

par Olivier C

May 08, 2020

Useful if you are already comfortable with deep learning and you want to learn how to use the (great) pytorch package. If you want to learn about deep learning from scratch, the explanations are not very intuitive and skip over some very interesting features.

par Chaney O

Jun 02, 2020

The lectures and quizzes are too short to provide much value. The material could be better condensed. The labs were useful, although at times, it felt like the same material from a prior video. In general, it was a good overview.

par Mohammed A S

May 05, 2020

This course provides a good amount of knowledge of PyTorch. However, the explanation and presentation are really bad. The monotonous voice and the quick changing of slides forces learners to watch the videos again and again.

par Sabrina S

Mar 09, 2020

Ok walkthrought of pytorch, a lot of content but slight mismatch between rather basic DS topics and advanced programming skills. Materials need to be reviewed for spelling and grammar, some quiz questions are unclear.

par Yi M L

Oct 28, 2020

the content is definitely overloaded.. i am blowing.. felt like i went to college again. if cut some of the content it will be much more user friendly to learn.. for an online class prespective

par César A C

Jun 25, 2020

The course is quite complete, but it contains to many things already contained in the previous courses within the Specialization. The final honor part could have been much better.

par Geir D

Mar 08, 2020

Presenter is a synthesized computer voice. Slides and exercises are full of spelling errors. Contents is OK, but presentation is not very inspiring.

par Tony D

Sep 08, 2020

Very slow and redundant material with previous courses of the "IBM AI Engineering Certificat Professionnel"

par Mutlu O

Aug 04, 2020

More useful exmples in labs would be helpful to understand the possibilities with the method and tool

par Miroslav T

Jun 08, 2020

quality of videos at the beginning of course are low, fells like the machine is reading it

par Benhur O J

Jan 30, 2020

To focus in the coding but not the underlying structure of the library and how to use it.

par Prateeth N

Jul 01, 2020

Very Basic course. Would have enjoyed more interesting examples in the notebooks

par Bhaskar N S

Apr 04, 2020

Found it very difficult to follow some of the content and assignments

par Pakawat N

May 05, 2020

There are a lot of mistakes in the slides and video but no updates

par Suman S

May 03, 2020

The course is too heavy to have just one project.

par 谭皓博

Jul 15, 2020

A number of mistakes were found in the course.

par Roger S P M

Mar 31, 2020

The course material contains some really fantastic information, graphics, and programming assignments. However, the presentation of this material is absolutely terrible! It seems they intentionally tried to make the presentations as boring as possible. The lectures are monotone, the 15 second opening scene is annoying, and the content focuses 70% on the concepts of Deep Learning (which is fine) and 30% on PyTorch. So when you finish you do not feel very skilled with PyTorch.

Finally, ALL of the student complain that the programming environment is very often offline. You cannot do many of the assignments because the "Cognitive Classroom" is usually not working. However, the last lecture f each week contains the Jupyter notebooks for the assignments. You can download and then run them in some other environment like Google Colaboratory or IBM Watson Cloud. Also, most of the programs contain a programming omission that the students have to fix every time. The instructors have not fixed the problem which has been reported to them. So pay attention for the "Pillow Error" in Week 3 because you will be fixing it yourself in most assignments for the next 4 weeks.

par Ben A

Aug 05, 2020

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 deeplearning.ai or fast.ai course.

par Calvin W Y C

Mar 11, 2020

The general content of the course is good. However, I was experiencing a lot of problem accessing the lab platform. Also, there are typos and grammatical mistake everywhere in the quizzes. The audio of the video are done using computer generate voice over, instead of a real person speaking. I think the instructor of the course doesn't speak fluent English, which is understandable why computer voice over is used instead, but the non-stopping speech makes me a bit hard to concentrate sometimes.

par Iain G

Apr 02, 2020

The quizzes are a complete joke. If you're hoping employers will take Coursera certificates seriously, the standard of assessment here is not good enough by a long long way.

par Alex D

Oct 05, 2020

Very technical and math-oriented. Even after completing it, I have no idea how to apply it to the real world. Seems everything is read using a computer voice.