Chevron Left
Back to Convolutional Neural Networks in TensorFlow

Learner Reviews & Feedback for Convolutional Neural Networks in TensorFlow by deeplearning.ai

4.7
1,953 ratings
272 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

JM

Sep 12, 2019

great introductory stuff, great way to keep in touch with tensorflow's new tools, and the instructor is absolutely phenomenal. love the enthusiasm and the interactions with andrew are a joy to watch.

MH

May 24, 2019

A very comprehensive and easy to learn course on Tensor Flow. I am really impressed by the Instructor ability to teach difficult concept with ease. I will look forward another course of this series.

Filter by:

26 - 50 of 270 Reviews for Convolutional Neural Networks in TensorFlow

By Asad A

Aug 23, 2019

Learnt a lot and believe me this is perfect way to teach.

By behnoud

Aug 20, 2019

thanks,,,thanks,,,thanks,,,this is the biggeset revolution in tensorflow,,,thanks Laurence

,,,thanks andrew because of this course

By Chintada A

Aug 21, 2019

really nice introduction to CNNs

By Antoreep J

Apr 21, 2019

In the workbook section, the question colab notebook opens up the answer notebook, please rectify the same.

By Edir G

May 11, 2019

It's great to learn about data augmentation techniques and how to implement this. This is a great complement for the deeplearning.ai's course on Convolutional Neural Networks.

By Paweł D

May 15, 2019

Pretty basic level, aimed rather to beginners.

By Kaustubh D

Aug 06, 2019

This course is taught excellently, but there is very little content at least from a programming point of view. There was no need of an extra week for only specifying the differences of binary and multi-class classification in code. Rather, there could have been more covered if codes of different output structure like object recognition where the output is not a flat map could be covered. If it has been purposely done to keep the course open to even newbies in Machine Learning, then there should have been a course focussed for those who have done Andrew Ng's ML/DL specialization.

By Walter H L P

Aug 06, 2019

This course is so short in content that, in the whole last week, it is explained a trivial concept about multi-class classification. Besides, the last quiz recycle questions from the previous quizzes from this and the previous course. It is clear that the course was made in a hurry once the notebook examples lack in written content or figures explaining the subject. Finally, there is no practical assignments in this "Tensorflow in practice" course.

By Alaso L K

Jun 14, 2019

Hands on practice and I love the videos after each lab that explains all we encountered during the lab. I highly recommend this course to anyone interested in CNNs

By Eddy P

Jun 19, 2019

Very hands-on experience learning through this course. But only with a little of content each week comparing to the deep learning specialization by the same organization.

By Gogul I

Jun 22, 2019

Amazing course to learn concepts such as Dropouts, Augmentation and Transfer Learning to solve real world image problems.

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 Adam

Jun 20, 2019

Clearly explain for CNN

By Akhil K P

Jun 22, 2019

This course worked as a great reference for my project on Neural Networks. This is one of the great and well-structured course.

By Yuanzhe L

Jun 25, 2019

Great course!

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 Leo

Jun 25, 2019

Great course for Computer Vision problems!

By SAHARSH A

Jun 26, 2019

compel the submission of ungraded tests

By Nazarii N

Jun 27, 2019

Easy and clear

By Pachi C

Jun 26, 2019

Great course and fantastic professors (Laurence and Andrew)

By Eagle Y

Jun 27, 2019

I really love this course! It is a lot of fun and I highly recommend this to other people.

By Magomet A

Jul 01, 2019

Great course! Learned a lot about CNNs

By saket p

Jul 01, 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 Sergei A

Jul 02, 2019

All is clear and simple.

By Aniruddha S

Jul 03, 2019

Nice Course but little tricky when making directories.

Learned so much.