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Learner Reviews & Feedback for Convolutional Neural Networks in TensorFlow by deeplearning.ai

4.7
2,001 ratings
282 reviews

About the Course

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....

Top reviews

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.

SS

Dec 09, 2019

Very clear explanation on the concepts at the higher level and practical application of it is discussed, demonstrated and also the exercises are of the same way. You will just love learning this way

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201 - 225 of 280 Reviews for Convolutional Neural Networks in TensorFlow

By Guilherme R M

Jun 10, 2019

Bom curso, muito prático.

By Yufei M

Jul 26, 2019

I think the quiz should be harder

By ashraf s t m

Jul 31, 2019

Voice is low

By João A J d S

Aug 03, 2019

I think I might say this for every course of this specialisation:

Great content all around!

It has some great colab examples explaining how to put these models into action on TensorFlow, which I'm know I'm going to revisit time and again.

There's only one thing that I think it might not be quite so good: the evaluation of the course. There isn't one, apart from the quizes. A bit more evaluation steps, as per in Andrew's Deep Learning Specialisation, would require more commitment from students.

By hamzeh a

Aug 06, 2019

Very Cool

By Sharvil G

Aug 06, 2019

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

By Michel M

Aug 06, 2019

The final assignment was somewhat a steep step

By Prabesh G

May 23, 2019

Okey.. So easy but okey

By 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.

By 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.

By 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.

By Xiangzhen Z

Aug 18, 2019

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

By Muhammad U

Aug 18, 2019

A well taught course with interesting coursework and projects

By 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

By 陈浩然

Sep 05, 2019

Please transfer the notebook from CoLab to Coursera.

By Dr. H H W

Sep 06, 2019

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

By Kailyn W

Sep 09, 2019

I need more coding practice, not just quizzes.

By Xinhui H

Sep 16, 2019

Some overlap with first course.

By 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.

By Marcos V G J

Sep 25, 2019

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

By 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.

By Phuoc H L

Nov 14, 2019

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

By Sebastian M A

Dec 06, 2019

No le pongo las 5 estrellas por la falta de ejercicios prácticos calificables.

By Muhammad U

Dec 07, 2019

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By Vitalii S

Nov 25, 2019

Too easy with good background and fast passing course.