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

4.7
stars
6,988 ratings
1,088 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

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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976 - 1000 of 1,090 Reviews for Convolutional Neural Networks in TensorFlow

By Moeen T

Feb 19, 2021

There wasn't enough useful content. There were also many problems with the programming assignments, specially in the last week's assignment.

By Alejandro B G

Sep 3, 2019

Google colab system for tasks is pretty bad, no control on the tasks plus it erases and u can't prove you did the work unless you save it

By ABHAS B

Apr 9, 2020

The course content is excellent. The talks with Andrew are inspiring, but the assignment graders are aweful and a big turn off.

By Ameya D

Jun 17, 2020

This course is more of hands on activity in tensorflow. You need to have good understanding of CNN prior to doing this course.

By Amit C

Mar 18, 2020

Content is very limited.I wish they could have gone in-depth covered more areas of CNN like object detection ,segmentation etc

By Jingwei L

Aug 30, 2019

The course is taught excellently. However, there are overfull file stream operations in Python that the course does not cover.

By Harri V

Jan 26, 2021

Week 4 final assignment was quite bad, because there was new Python/Numpy stuff which was not covered at all in the course.

By Marc-Antoine G

Nov 13, 2019

Please make the "Ungraded assignment" Graded and add more comments/directive in them to make sure we understand each steps.

By Samuel K

Nov 2, 2019

Clear explanations. Good sample codes. Too easy. Doesn't go deep enough in terms of theory. Exercises should be mandatory.

By Daniel D

Mar 26, 2020

Pros: the course teaches CNNs clearly and concisely.

Cons: the memory issues on the last assignment wasted a lot of time.

By David H

Nov 16, 2019

Not solid enough and the exercise could be more organised. For example: some of the data downloading links didn't work.

By Shreenivas

Dec 22, 2020

Good content. The coding and assignments need significant improvement. There is no support whatsoever in assignments.

By Sailesh G

Nov 2, 2019

Expected a lot more in this course from the Tensorflow specialization. Something that'd take us beyond tf.keras.

By Daniel Y

Feb 27, 2021

Disappointing. This is more like Python course. Deep Learning specialization CNN course teaches you x100 more.

By Mohammed F

Jul 6, 2019

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

By Alexey V

Nov 22, 2019

complex ideas in very basic tasks that you can easily accomplish by copy-pasting from provided notebooks.

By Shubham A G

Aug 25, 2019

Lacks depth and complexity. The course is geared more towards complete newbies or high school graduates.

By Frank W

Jul 17, 2020

The programming tasks are not very helpful. The main difficulty is that unknown methods should be used.

By Michael E

Feb 14, 2020

Would like to have seen some information on techniques such as batch normalization and residual layers.

By Apichart L

Jul 5, 2021

Not well-design, it is very light information and knowledge to learn, unlike the #1 introduction.

By Nahum P

Sep 22, 2020

Final work had almost no connection to what you learned during the course.

Not enough hands on.

By ROSS

Oct 15, 2021

The knowledge taught in the course is over-simplified. The assignments are not well-designed.

By Geoff G

Aug 17, 2020

The topics are explained very briefly.There is no in depth coverage of the mentioned topics

By Yu S C

Jun 26, 2021

I dont think this course is very helpful in terms of price/how much you can learn.

By Sajal C

Mar 31, 2020

Course is good however there can be programming assignments for better practice.