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Learner Reviews & Feedback for Convolutional Neural Networks in TensorFlow by DeepLearning.AI

6,186 ratings
957 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 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....

Top reviews

Nov 12, 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!

Mar 14, 2020

Nice experience taking this course. Precise and to the point introduction of topics and a really nice head start into practical aspects of Computer Vision and using the amazing tensorflow framework..

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351 - 375 of 949 Reviews for Convolutional Neural Networks in TensorFlow

By Muhammad A A K

Dec 20, 2019

I ready enjoyed learning this course. It was truly awesome.

By Pachi C

Jun 26, 2019

Great course and fantastic professors (Laurence and Andrew)

By Alistair W

Apr 23, 2020

Great course - easy to follow. Clear, concise and fun! :-)

By Peter B

Sep 13, 2019

An amazing course that was written by masters of the field

By Muhammad h

May 8, 2020

Amazin Experience was with course tutor. I love coursera.

By Thrilok N

Apr 5, 2020

So much learning in a very short period, feeling amazing.

By Andrew S

Feb 25, 2020

Great course! Really helped me learn the basics of keras.

By Banu B

Aug 29, 2020

The teacher is so amazing!! The content was fun to learn

By Leo C

May 3, 2020

Very little info overall, but also very quick to finish.

By Sachin

Feb 14, 2020

The Way this has been driven, I never felt disconnected.

By Max W

Dec 2, 2019

Excellent structure and code alongs with great examples!


Aug 14, 2019

An awesome opportunity to learn CNN and its application.

By Isaac A A

Aug 5, 2020

The concepts are quite straightforward and enlightening

By Nguyen T V

Jun 6, 2020

Thank you very much. This course is very useful fro me.

By Julian R

Apr 11, 2020

Muy buen ! Cubre lo fundamental y tiene ejemplos claro!

By Vineet K

Apr 11, 2020

Content and assignments were very relevant and helpful.

By Mukkul N K

Nov 22, 2019

Very nice course. I learned many wonderful techniques.

By Bandelier L

Nov 19, 2019

Nice because very quick to have good efficient basics !

By Shweta S

Jul 16, 2019

very good content and every point are explained nicely.

By Guillermo R

Oct 31, 2020

Good course for computer vision, challenging exercises

By Eduardo J M G

Sep 17, 2020

An excellent course to keep learning about AI and DNN.

By Juan E R

Jul 30, 2020

excellent course, great techer, all concepts explained

By Moinul I

Jul 26, 2020

Great explanation of everything. I have learned a lot.

By Kevin R

Apr 29, 2020






















ce teaches simple and convincing.

By ongole s s

Apr 21, 2020

learnt how to work on real projects in computer vision