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Voltar para Convolutional Neural Networks in TensorFlow

Comentários e feedback de alunos de Convolutional Neural Networks in TensorFlow da instituição

6,070 classificações
926 avaliações

Sobre o curso

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the TensorFlow Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Melhores avaliações

12 de Nov de 2020

A really good course that builds up the knowledge over the concepts covered in Course 1. All the ideas are applicable in real world scenario and this is what makes the course that much more valuable!

11 de Set de 2019

great introductory stuff, great way to keep in touch with tensorflow's new tools, and the instructor is absolutely phenomenal. love the enthusiasm and the interactions with andrew are a joy to watch.

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651 — 675 de 921 Avaliações para o Convolutional Neural Networks in TensorFlow

por Marco D G S

25 de Jul de 2020

I think some parts of the assignments are not really the main objective of the course, they focus more on methods that involve just creating folders and copying files, which is not what I was there for. Aside from that, great ML content right here :)

por Oscar D D L T

7 de Set de 2020

Excelente curso, casi no necesitas saber programar los conceptos super actuales y las actividades te permiten ejecutar procesos de inteligencia artificial y lograr resultados interesantes con un conocimiento tecnico minimo....super recomandable!!!!!

por Saeif A

20 de Ago de 2019

This is another great course in the specialization. I wish only there were graded exercises like the previous course that we can submit and get a grade for. I understand maybe this is due to the long time of training and that is not possible to do.

por Voltaire L

15 de Jan de 2021

The final project was missing some prompts for additional code. I'm all for research but there should be a heads up that we won't have all the prompts we need, since all the tests before specifically asked for the code needed to pass.

por Thomas L

4 de Nov de 2019

Maybe a bit repetitive, when you just finished Course 1. We see a lot of lines of codes explained again from course 1 and I think that could be avoided.

However, the new concepts are nicely introduced and very interesting to implement!

por Alvin M

27 de Out de 2020

Sudden spike of difficulty and approach in the final assignment, but overall, the pacing is really nice. You really can't solve the last assignment without reading the discussion forum or looking for things for yourself though.

por William G

16 de Ago de 2019

It was good, but similar to other learners I feel a little light in content. Though in tandem with the deep learning specialization gives a good view on convolutional neural networks as well as its implementation in tensorflow.

por Leon R

26 de Out de 2019

Loved the course. I would have liked a module on saving your own models and then loading them later. The Inception one is nice, but it comes with some "niceties" that I don't think you have with loading a home grown model.

por Humberto N

9 de Jun de 2019

It's an great course with simple explanations about the Deep Learning topic. It's a perfect fit for beginners or those who want to have a practical review before starting using Tensorflow 2.0 with keras implemetations.

por Varun K M

27 de Abr de 2020

It was a great course but there wasn't much theory into explaining why and what's happening. A course to get started with the coding without actually needing to require what is happening in the background.

por Kalana A

14 de Abr de 2020

Nice course. Even though I have previously done some projects using CNN and multi-class classification still this course let me to have an insight to how these APIs work. Keep Up The Good Work!!!!!!

por Fahmi J

29 de Abr de 2020

This course awesome, but the notebook from coursera "i think" doesn't support any experiment we want, so we have to do it on google colab. But great, limitation is okay as long it's still graded

por XX N

2 de Out de 2019

The course is really nice. But would be better if the convolutional layers were a bit more detailed. It was a bit difficult for me to understand all the parameters e.g: input/output filter size.

por luis a

29 de Set de 2019

The course was fine sometimes I feel too easy. I would like to see more of the available options for the layers, such as padding, stride. filter size, mean average, batch normalization, etc...

por C A

23 de Dez de 2020

Assignments are good, but it should concentrate more on the actual problem rather than the file reading or any nitty gritty details without any hint. Thanks , this course is good in overall.

por Rajesh R

14 de Jun de 2020

Great course to learn newer aspects of TF. For me a great revision of ConvNets and a confidence builder. If there's one thing I'd fix, it would be the autograder and how often it crashes.

por Amit K D

24 de Set de 2020

Found the hands-on not very interesting. Couple of them focussed on file handling and stuff rather than on more important stuff that getting into the hoods of transfer learning, etc.

por Rakesh G

16 de Jan de 2020

I think this was a good course but the standard of exercises and quizzes was too easy. More conceptual questions especially in quizzes would help in understanding the topic better

por ashish s

22 de Abr de 2020

Overall good. Could have gone in bit more depth on how various hyper parameter tuning and regularization methods impact the model training. Provide some best practices tips .

por Gerardo S

26 de Set de 2019

the last exercise needed a big upload, made it imposible (for me) to do. This was a problem not related to the subject, should use data downloadable directly from internet.

por Eric L

10 de Dez de 2020

This course only requires few hours of work and I would like to see more depth. The parts on image augmentation and transfer learning were pretty interesting though!

por Luciano C

31 de Dez de 2020

Curso muito legal, a única coisa que ficou um pouco abaixo do esperado foi o último exercício da quarta semana, não foi construído com o cuidado visto nos outros.

por Vishwanadha K V

22 de Jun de 2020

The assignments are not challenging enough. The concepts are really well explained and for someone with no background in this area, this is a great learning asset

por Dimitry I

10 de Ago de 2019

Very good course that teaches you basics of convolutions, augmentation, transfer learning. Thank you to Mr. Moroney and the Coursera team for making it available.

por vaibhav t

26 de Jun de 2020

The course was good. The only problem was the last assignment where some of the functions went missing. It was difficult for a beginner to catch such glitch