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

4.7
stars
8,150 ratings

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 DeepLearning.AI TensorFlow Developer 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 Developer 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

MS

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!

RB

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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926 - 950 of 1,262 Reviews for Convolutional Neural Networks in TensorFlow

By Dimitry I

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 vaibhav t

Jun 26, 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

By chaitanya m

Apr 15, 2020

The best course to do. Especially after the specialization course from Andrew. It is really helpful to code all the concepts you learned from Andrew course.

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 Moritz R

Jan 24, 2021

Very nice the step from the first course was really nice. The achievements were harder to reach an all over the cose was less buggy than the first one. :)

By Shubham G

Jan 29, 2022

Last coding assignment was not clear. Eg- Why is there a model.evaluate line at the end when we are already checking validation accuracy in fit generator

By Estefania T

Jun 2, 2020

The contents are a bit light from my point of view. I get it is to be accessible for more people but math and explanations are in some cases important

By Toqa A M

Apr 4, 2021

it was great course but I need some more details and the speaking was a little difficult as some of words are slang and the translation was so bad

By Subham S

Dec 23, 2019

The course content was quite good and overall understandable but the exercises and quizzes were quite easy, they could have been more challenging

By Pray S

Apr 23, 2020

The hand sign assignment need more explanation about using flow object from ImageDataGenerator since I just know only flow_from_directory object

By Jossent

Feb 14, 2021

Learn a lot for CNN in this course, but require advance knowledge in Python & Numpy to understand the code as it was not explain in the course.

By Qu Y

Nov 28, 2020

Exercise_4_Multi_class_classifier_Question-FINAL has problem if you entirely follow the tips, you can find the correct code in the forums.

By Gianluca T

Sep 17, 2020

Very nice and interesting videos, cool concepts, amazing datasets. Exercises lack sometimes clear objectives, or provide unclear feedbacks

By Rodolfo V

Jul 10, 2020

I guess one thing was not studied, the method .flow() which get the images generated by keras with the dataset labeled for the final test.

By Caroline B

Jul 14, 2022

The tutorials were easy to follow and I think the assignments were nice because some parts were easy, but some parts had some challenges.

By Shubham S

Dec 6, 2020

Lectures videos are amazing but the only problem in programming assignments. Programming assignments should have been properly designed..

By Abhiram

Mar 12, 2020

More detail videos or links,examples for important techniques like dropouts and for like multi class classification which may be optional

By Madhu

Dec 13, 2020

Content was great. It was insightful. However I felt, in few assignments, the instructions were misleading and took some to figure out.

By Ghifari A F

May 14, 2020

The course is very useful for practical purposes. But this course didn't cover some advanced topics such as object detection and GAN.

By Nikos R

Oct 19, 2020

Very good course to get you started on convolutional neural networks. Week two had a small problem with the programming assignment.

By Brian ( B

Oct 23, 2019

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

By Revant T

May 20, 2020

Programming assignments could have been better. The programming assignments at the end of each week were not challenging enough.

By Hang N

Feb 26, 2020

This course offers more executable functions than actually helping you understand (in-depth) how neural network really works.

By Parikshit N

Jul 12, 2021

Good content and Lawrences technique was great. But it took a bit longer where assistance was required during assignments.

By Przemysław D

Sep 27, 2019

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