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

7,066 ratings
1,102 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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101 - 125 of 1,102 Reviews for Convolutional Neural Networks in TensorFlow

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.


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.

By Tanay G

Apr 8, 2020

I found the course really interesting and I learned a lot. The thing I liked the most about this course is the minimal helping nature of the evaluative notebooks, deep learning specialisation's notebooks practically spoon-fed the answers.

By arnaud k

Jun 25, 2019

The practical aspect of this course is addicting. I can't stop myself from wanted to try the next technique. maybe because i have seen most of these before but i going had made it clear what i was doing wrong in some of my "failed kaggle"

By Jafed E G

Jul 6, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

By Carlos V

Jul 7, 2019

Excellent course, in particular, all explanations to work with the Image Augmentation libraries, I enjoined the transfer learning part, highly recommended for anyone looking to improve their knowledge of Convolutional Neural Networks

By Nelly N

Nov 25, 2021

It is a great course to learn about Convolutional Neural Networks, exploring how to use them with large datasets, Augmentation, Dropouts, Regularization and Transfer learning, and coding during binary or multi-class classification.

By Harun U F

Mar 31, 2021

Deeplearning.AI allows me to explore more about CNN. Using CNN and Tensorflow, I can build a model in just few lines of code. This library really helps me to overcome the problems in Machine Learning, especially in Computer Vision.

By Zeeshan A

Jun 25, 2020

The specialization covers brief introduction to the concepts of Computer Vision and Natural Language Processing. It introduces to TensorFlow and gives a hands-on practical experience over the tool through simple assignments.

By Vishakan

Apr 22, 2020

Learnt a lot of new things about image classification, how to better predict images using TensorFlow. Laurence Moroney is a great teacher who skillfully explains the code and its significance in an easy-to-understand manner.

By Surya K

Apr 5, 2020

Incredible course structure. Really well designed and thoughtful. The programming assignments were especially very helpful. Grateful to Coursera for letting me do this specialization during these uncertain times of COVID-19.

By Steven J R

Mar 24, 2021

It's a nice approach and a good example of how we're going to do Machine Learning stuffs through an open-source library called Keras from Tensorflow (from Google ofc). Thanks, Google and DeepLearning.AI., Mr. Andrew Ng!

By Sawyer S

Jun 22, 2020

Very instructive and practical, but the coding assignment can be mis-leading from time to time. However, that is not anything out of ordinary, practitioners should expect some level of sophistications in real life

By Low W T

Aug 9, 2020

Coming from an aspiring Data Scientist, Laurence Moroney provided succinct explanation on practical aspect for CNN, which is a definitely a supplementing course material alongside's specialisation.

By Rakshit A

Feb 22, 2021

very well explained and the google colab notebook that they share is very helpful . i recommend to go through the lectures and go through youtube videos for deeper understanding before just jumping to exercises.

By Chirag G

Mar 8, 2020

This specialization is really helpful. I had done other specializations and Machine Learning Course of Andrew Ng. But this course helped me to revise those topics as well as implement them in the real world.

By Sharan S M

Oct 22, 2019

After finishing this course, I was able to build a neural network that could identify different types of boats with around 94% accuracy. I used many techniques learned in this course like image augmentation.

By Reza M

Aug 28, 2021

T​his is a very good course to start on TensorFlow. It requires certain amount of knowledge ( I recommend Deep Learning Specialization). I started kaggling after this course and the results are very decent.

By Vincent H

Nov 26, 2019

IT is a great course about Deep Learning and above all, how to code it with Python.

It is very practical and you learn a lot of features about the Tensor Flow framework that you can reuse for other issues.

By MD. A K A

Mar 28, 2020

Really enjoyed the course. Thanks team. Except "Inception" every topic was clearly practiced. For "Inception", I am eager to learn how to lock a model & how he trained weight can be saved.

By mcvean s

Nov 13, 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!