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

4.7
1,960 classificações
273 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 deeplearning.ai 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 deeplearning.ai 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

JM

Sep 12, 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.

PS

Sep 14, 2019

An excellent course by Laurence Moroney on explaining how ConvNets are prepared using Tensorflow. A really good strategy to have the programming exercises on Google Colab to speed up the processing.

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201 — 225 de {totalReviews} Avaliações para o Convolutional Neural Networks in TensorFlow

por hamzeh a

Aug 06, 2019

Very Cool

por Sharvil G

Aug 06, 2019

Transfer learning part should have been in more detail. Thanks.

por Michel M

Aug 06, 2019

The final assignment was somewhat a steep step

por Oleksiy S

May 23, 2019

Exellent tutorial for using Tensorflow and convolutional networks. Useful usage examples, interesting and challenging exercises. A few minor mistakes prevent five star grading. But please note that mistakes happen and we have to live with this :-). Nice work, looking forward for the next course of the specialization.

por Prabesh G

May 23, 2019

Okey.. So easy but okey

por Humberto d S N

Jun 09, 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 Super-intelligent S o t C B

Aug 10, 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 William G

Aug 16, 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 Xiangzhen Z

Aug 18, 2019

a little bit too easy compared to Andrew Ng's deep learning course.

por Muhammad U

Aug 18, 2019

A well taught course with interesting coursework and projects

por Saeif

Aug 20, 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 Zhi Z

Jul 06, 2019

A good course for Keras but not for tensoflow.

por Nicolas

Aug 30, 2019

First, I think the course was great, very instructive. Thanks to Andrew and Laurence for putting this together, is a great source of information to understand more about DL. Some things I think could improve the course.

I found the transfer learning lessons a bit unclear and I struggle generalizing this to other cases. Also, I was a bit confused by the flow of the course. The course starts with a multi classifier (or actually, the previous course), then the lessons focus on binary classifiers and it ends again with multi classifiers, because these should be the more complex ones.

One last technical thing, only on the last lesson of this course it is mentioned that the classifiers output the probabilities on alphabetical order when using ImageDataGenerators (or at least, that's my impresision). I've wondered since the course introduced the ImageDataGenerators, how the probabilities are assigned on the outputs. I could figure out on the sigmoid that the classifier would look for the first class on the directory and output 1 or 0 based on that, but it would be good to have this mentioned at some point on the video when the ImageDataGen is introduced.

Thanks again! Great course

por 陈浩然

Sep 05, 2019

Please transfer the notebook from CoLab to Coursera.

por Dr. H H W

Sep 06, 2019

Great insight for the practical aspect of TensorFlow, add value on top of Andrew's DL courses.

por Kailyn W

Sep 09, 2019

I need more coding practice, not just quizzes.

por Xinhui H

Sep 16, 2019

Some overlap with first course.

por Anand H

Sep 12, 2019

One challenge i have faced is with deploying the trained models. I find very little coverage on that across courses. It's one thing to save a model.h5 or model.pb. It would be nice if you can add a small piece on deployment of these models using TF Serving or something similar. There is some distance between just getting these files outputted and deploying. TF documentation is confusing about some of these things. Would be nice if you can include a module on that.

por Marcos V G J

Sep 25, 2019

Good content, but lacks exercises that forces us to code ourselves to solve the problemas

por Donal B

Oct 18, 2019

Excellent course. Would have liked graded coding assignments like in the first course.

por luis a

Sep 30, 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 Gerardo S

Sep 27, 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 Przemysław

Sep 27, 2019

Instructors are really good, but in my opinion, this course should contain Object Detection and Object Segmentation topis.

por H M A r

Oct 02, 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 KHODJA

Oct 02, 2019

A more advanced course would be highly appreciated.