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Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 1,829
Рецензии: 254

О курсе

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....

Лучшие рецензии


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.


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 из 254 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: 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.

автор: Xinhui H

Sep 16, 2019

Some overlap with first course.

автор: 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

автор: Thomas L

Nov 04, 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!

автор: 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...

автор: Przemysław

Sep 27, 2019

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

автор: 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.

автор: 陈浩然

Sep 05, 2019

Please transfer the notebook from CoLab to Coursera.

автор: Dr. H H W

Sep 06, 2019

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

автор: Kailyn W

Sep 09, 2019

I need more coding practice, not just quizzes.

автор: KHODJA

Oct 02, 2019

A more advanced course would be highly appreciated.

автор: 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.

автор: 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.

автор: Vittorio R

Oct 06, 2019

Good, but expected more, for example object detection.

автор: Damon W

Oct 08, 2019

Good practical course. A bit heavy on visual images, but very informative.

автор: Marcos V G J

Sep 25, 2019

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

автор: Donal B

Oct 18, 2019

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

автор: Brian ( B

Oct 23, 2019

very practical courses on implementation of CNN in tensorflow. Suggest student also take the deeplearning series with this series.

автор: Leon R

Oct 26, 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.

автор: Lei W

Oct 30, 2019

will be nice to have non-third party programming exercises that are graded by Coursera

автор: Bingcheng L

Nov 12, 2019

quite easy

автор: Phuoc H L

Nov 14, 2019

More exercises should be available for students to practice and test their skills.

автор: Ujjwal G

Nov 16, 2019

I think most much of the course conent was same as the first course, this course could have been a little more advanced. But overall a great place to start.

автор: Mohammed F

Jul 06, 2019

Could have dived more into the details and inner workings of Convolutional layers but overall awesome course.

автор: Luiz C

Jun 11, 2019

not challenging enough