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

4.7
stars
8,024 ratings

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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426 - 450 of 1,245 Reviews for Convolutional Neural Networks in TensorFlow

By Suraj

Feb 27, 2021

Amazing intuitive explanations by Laurence moroney sir 🙌🏻

By Alexey A

May 31, 2020

Great course! Especially final programming task is the best

By Shubham

May 11, 2020

It was a relatively easy course but a good one nonetheless.

By Muhammad A A K

Dec 20, 2019

I ready enjoyed learning this course. It was truly awesome.

By Pachi C

Jun 26, 2019

Great course and fantastic professors (Laurence and Andrew)

By Mohsen P

Nov 30, 2021

It is a practical course for computer vision applications.

By Pravin B

Feb 26, 2021

Excellent course to brush up the knowledge and learn more.

By Alistair W

Apr 23, 2020

Great course - easy to follow. Clear, concise and fun! :-)

By Peter B

Sep 13, 2019

An amazing course that was written by masters of the field

By p g

Aug 23, 2023

Great learning material as always in that set of courses!

By Idriss C

Jan 2, 2022

Very informative as an introduction to image processing/

By Ngọc L L

Oct 5, 2021

nice course, explain really clear and easy to understand.

By Allan H

Sep 19, 2021

Well explained and quite thoughtful. Thanks Dr. Moroney!

By Developing T

May 8, 2020

Amazin Experience was with course tutor. I love coursera.

By Nagamalla T

Apr 5, 2020

So much learning in a very short period, feeling amazing.

By Andrew S

Feb 25, 2020

Great course! Really helped me learn the basics of keras.

By Phạm Đ T

May 5, 2021

This course help me a lot to practice in Neuron Network.

By Banu B

Aug 29, 2020

The teacher is so amazing!! The content was fun to learn

By Leo C

May 3, 2020

Very little info overall, but also very quick to finish.

By Sachin

Feb 14, 2020

The Way this has been driven, I never felt disconnected.

By Max W

Dec 2, 2019

Excellent structure and code alongs with great examples!

By WERE, D W

Aug 14, 2019

An awesome opportunity to learn CNN and its application.

By Abhinav t

Jan 25, 2024

A Great course for Tensorflow certification preparation

By Bruno R S

Jan 24, 2023

Good introduction to convolutions in a practical sense.

By Isaac A A

Aug 5, 2020

The concepts are quite straightforward and enlightening