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

4.7
stars
5,797 ratings
877 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

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..

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!

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76 - 100 of 871 Reviews for Convolutional Neural Networks in TensorFlow

By Sagar P

Aug 24, 2020

Precise and to the mark. Good brief up of the concepts. 5 stars for ease of implementation through programming assignments. Suggestion to fellow learners: Couple these courses with those by Andrew Ng, so it would be the best merger of theory + implementation. Laurence Moroney never fails individual's expectations. :)

By Mateus d A D P

Oct 19, 2020

This course presents a more in-depth look at CNNs in comparison to the first one of this specialization. Subjects as Image Augmentation, Data Generators and others are taught about. The only thing I didn't find quite right is the final assignment. I could be wrong here, but it seems it wasn't designed properly.

By Ara B

Aug 19, 2019

Easy to follow. a lot of examples. I was expecting at least one assignment for the final! :)

As for the convolution we never talked about DOG+SIFT or other feature extraction techniques. Also I would like to see how we can separate an object of interest from background e.g. using clustering or a video stream.

By ALVARO M A N

Dec 9, 2019

I love this, because the instructor make the difficult easy. After ending this course, I believe I would enrolled on the other specialization, to gain a better mathematical understanding of convolutional neural networks but I'm pretty happy to learn the practical stuff, this make possible a lot of projects!

By Deepak V

May 2, 2020

This course builds on the previous introductory course in the Specialisation. Not only do the four exercises provide practice towards neural network implementation, they also provide a chance to use Python for organisation and manipulation of data, pre-learning.

A fantastic and concise course over all.

By Aditya W

Jan 22, 2020

I mainly to learn the various constructs to do various things in TensorFlow, and this course is very well constructed for it. It doesn't explain the actual mathematics though, and I don't blame it for that. It is just designed to help people learn the framework. Overall, a very satisfying experience.

By Jian C

May 14, 2020

This course is a very good introduction to Tensorflow and CNN. I have taken Machine Learning theories at school and this is a very nice **programatic** supplement to my course. I think this would be even more helpful if I took it before I learn the theories. I would have been in less trouble then.

By KARAN S

Apr 10, 2020

It's amazing how far we've come in image processing. I remember using basic filters like sobel edge detector during my undergrad. And now we are here, being able to get SOTA results in just few minutes. I wonder how those Phds who were working on handcrafting filters ~2010 would have felt.

By anujeet

Dec 14, 2019

This course in tensorflow specialization is a must recommended. It builds knowledge from beginners to advance very smoothly, You will be able to get a experience of how to begin coding for tensorflow also be able to understand its core layers, And learning from Laurence is always fun.

By Sanjay M

Aug 13, 2019

Very well thought through course for Convolution Neural Networks using Tensorflow, covering some of advances topics like transfer learning, callback and review convolution layers. I already had understanding about CNN and these topics. This course shared scenarios when it is used.

By Thuyen T D

Aug 27, 2020

The course was amazing, but the thing i don't get it is the 'sparse_categorical_crossentropy' must be use in the last exercise notebook. In the video(s) ,Laurence introduced only 'categorical_crossentropy', hope somebody could upgrade the notebook to suitable the lessons. Tks.

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By Ozgur P

May 2, 2020

Really good course, but recommend doing deeplerning specialization first before doing this one or doing them together. Because Andrew Ng explains really well how convolutions work, and without this background info, it will be difficult to understand the concepts in this course.

By Syed A A

Aug 25, 2020

Really impressed by the work of the team. It is designed specially for the beginner to advance their career and be expert the emerging AI field. With the help of high quality videos and project based assignment one become expert hoe to deal and tackle real world problems.

By Simon Z

Sep 10, 2019

Excellent. I learned after a couple of years working with neural networks new topics and implementations. I think it would be a good idea to include also here an exercise that gets graded at the end such that we take our time and can try out if we can make things work.

By Abhinav S T

Jun 22, 2019

The week 1 is a bit casual but where as the remaining one's are just awesome learnt a lot like how to implement a model without overfiting and learnt how to implement transfer learning and multi-class classification problem, really worthy taking up this course....!!!

By Waqas A

Jul 1, 2020

This course is for beginners and intermediate, If you know the detail of the model layer then don't take this course. The instructor only tells the code who to add Conv, pool max layers in TensorFlow do not explain the depth of convolution and pooling layers.

By Shubham K

Aug 18, 2020

This was a really great course for me to dive into practising the implementation of machine learning for image datasets. The instructor is really nice. I thoroughly enjoyed the course and will be taking more courses on applied machine learning from Laurence.

By AKSHAY K C

Apr 6, 2020

The course was nicely built on the advanced topics of multi-class classification, data-augmentation, and transfer learning in Convolutional Neural Networks. Special congratulations to the instructor and his team for coming up with such a nice course.

By Mike B

May 11, 2020

The course was excellent. Other than the (typical by now) Coursera code-submission issues, the course really covers a broader range of CV applications & TF capabilities than I've seen with the "get it working and move on" workflow at the day job.

By Bartłomiej A

Aug 23, 2020

Thank you very much for this course, it helped me understand data augumentation and transfer learning. I am very inspired seeing computer graphic generated training data. It would be great having a separate course/workshop covering this topic.

By saket p

Jul 1, 2019

This is very well structured course for geeks who want to start learning machine leaning and implement different neural networks are hiking the technology world.

I personally appreciate the course material and instructor for the immense work.

By Rayhaan

Aug 13, 2020

Thank you for teaching me this outstanding course I learned a lot about Convolutional Neural Networks. The programming assignment were also at the right difficulty not too hard and not too easy. The quizzes were easy but really awesome.

Thanks

By Muhammad S

Jul 21, 2020

An excellent learning platform during Covd-19 pandemic. I appreciate the effort of the Coursera team who provide us such an amazing learning environment. This course really helps me to improve my practical knowledge of CNN.

Thanks Coursera.

By Nebojsa D

Aug 15, 2019

This lectures are givin a very nice advices for practical implementation of ConvNets. combining it with prof.Andrew Ng's lecture exercises in this course will allow you much more practi implementation of knowledge you have acquired before.

By Andrés P

Apr 21, 2020

The course in general is pretty good, only the last test seems to me that is incorrect, since there are 24 different classes, but doesn't approve it when you set it with these 24. It requires from you to put 26 when to me seems illogical.