Chevron Left
Back to Convolutional Neural Networks in TensorFlow

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

6,974 ratings
1,085 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..

Filter by:

1051 - 1075 of 1,087 Reviews for Convolutional Neural Networks in TensorFlow

By Matthew R

Dec 17, 2020

Very superficial look at deep learning. A lot of the programming assignments had little to no context.

By Francisco R G

Sep 29, 2020

Repetitive chapters, repetitive info on videos, and not very useful final test. They have to review it.

By Jin C

Sep 27, 2019

It's too easy for an intermediate machine learning leaner, and it's little about naive TensorFlow.

By Roger G A

Oct 11, 2020

Specially in week 4, big gap between information taught in the lecture, and the last assignment.

By Pouya K

Feb 9, 2021

poorly designed exercises

poorly designed material that all could be said in just 1 or 2 weeks

By Wingyuen P

Sep 23, 2021

Some notable omissions of key information in instruction, but mostly the exercises suck

By Jair N

Apr 5, 2021

The content are good, but the audio is low and the exercises are not well documented.

By Adith k

Jun 1, 2021

very basic.

There's hardly any video time. We can finish the whole course in a day

By Seyyed M A D

Aug 31, 2021

HWs are not well and thoroughly-thought designed (Grader runs out of memory ).

By Apoorv V

Aug 1, 2020

Average content. The last assignment for week 4 was structured quite poorly.

By Parth

Sep 12, 2019

coding assignment should be included otherwise it is easy to get certificate

By mukul k

Apr 4, 2020

expecting more advance topics instead of just using Keras.

By Lendixful

Aug 14, 2021

The jupiter notebook exercises are a mess, pls, fix them

By Oliver J

Nov 3, 2020

The last assignment is poorly designed and a real pain.

By Hanzhao L

Feb 11, 2021

The practices were poorly designed.

By Cynthia E

Mar 30, 2021

Assignments are not well designed

By Gunes D S

Jan 12, 2021

Very little content, ridiculously repetitive. Missing info in the last assignment made me waste a lot of time. I wouldn't mind spending time on that assignment if it had been actually challenging. Course designers should consider putting serious time and effort into the preparation of the hands on materials. There is some useful information in this course, but I passed without learning much because of poor design. I still have no idea how to design a good model based on the data set, how many filters to use in each convolution, how many layers in total, how many nodes in the dense layer, etc. The instructor keeps recommending "trial and error", which is fair but I would expect the discussions to be a bit more thoughtful and deeper than that, especially given the price of this "professional certification". This course is falsely advertised as intermediate level, it is actually introductory level, albeit being too simplistic compared to some other great substantial introductory level courses on Coursera.

By Alessandro S

Nov 3, 2020

Honestly this course was a bit of a disappointment, didn't really learn anything that can improve how effective i can produce a neural network, on the assignments the hardest parts was coding tasks that was never explained in the course, like reading and copying files, and that has not really anything to do on how to build a neural network, some of the examples provided did not really worked (as the accuracy was poor and always over-fitting), for the last assignment i cheated as using image generator lead to a really poor results so i just skipped and train the model using directly the images.

My suggestion spend more time on what strategy are used to improve the model when the results are poor as the model under-fit or over-fit, otherwise it looks like you add and remove layers until you got lucky.

By Fabian A R G

Jun 2, 2021

I am sorry for the 1 star but is time that deeplearningAI take course content difficulty a bit more precise. I know and I appreciate a lot what you are doing on spreading the knowledge of AI through many varied content, nonetheless if you put that the course is intermediate you should aim to make it intermediate. This is pre-introductory level course and I would have appreciated knowing that so I just skip it an go through a more advanced option. I still finished it as I already paid for it. It is still a well organized and fun course as usual, the problem is that this has absolutely no value in terms of "real world" examples as you put it...

By Tal F

Aug 13, 2020

What a disaster! I spent more time trying to game the scoring service into accepting a correct answer (and reading in the forum how other frustrated users managed to do it) than actually learning about tensor flow. Such a shame because there were some interesting topics. There is no TA answering questions in the forum either. It doesn't feel like any effort has been made to keep the course current and updated, addressing issues, etc. And the lab work was actually very repetitive - some were almost identical to previous ones.

By Brad G

Apr 4, 2021

Final lab was a total shit-show. Made you jump through hoops to run off and learn minor things which weren't covered in the course but were highly germaine to passing. Tons of technical problems with getting final lab to submit - reported by many users for over a year - never resolved by Coursera. But for the course itself, it was highly redundant - going into longwinded explanations over several videos of very simple things, often covered in the prior course.

By Maged A

Dec 5, 2020

Course is not properly structured. Transfer learning was using a very special case not the general case.

It is clear that course is just a collection for some scattered old videos and materials. You will realize that at the end of the course when you find that final assignment is NOT relevant at all to the material. Final assignment is a nightmare where there are no guidelines at all. There is no support at all from Coursera. it deserves 0 out of 5 not 1.

By Slav K

Sep 23, 2019

1) material is boiled down to no-brain

2) questionnaires have incorrect terminology (like method vs parameters)

3) with almost no mandatory assignment the value of certificate is dubious (see point #1)

4) Please stop marketing this course as about TensorFlow. it is all about Google's implementation of Keras and Keras only.

5) The code in course DOES NOT WORK with TF 2.0-rc. Thus student with 2.0 can't submit assignments.

By Joseph A

Dec 11, 2020

The course overall was great, but several notebooks were really frustrating, *especially* the final notebook in the course! There are literally 0 text cells that explain what is happening, 0 information on the goal, 0 information on the data we are working with, is it dogs or human or hand pictures? Are there 2, 3, 100 classes? Literally 0 information. This notebook was super frustrating to complete.

By Aladdin P

Aug 4, 2020

On the first course I gave more detailed feedback why I disliked the course, and unfortunately those ideas and feeling are even stronger with this one. Summary: The course is way too shallow and puts focus on many different things rather than what it should have done which is build on the deep learning specialization and do in depth focus on tensorflow.