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

4.7
stars
6,929 ratings
1,081 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..

JM
Sep 11, 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.

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1001 - 1025 of 1,078 Reviews for Convolutional Neural Networks in TensorFlow

By Pranav H

Dec 2, 2019

Coding exercises should be made compulsory and for the grade

By Eyal B

Feb 16, 2020

Didn't provide a real understanding for transfer learning

By MOUAFEK A

Jan 4, 2020

not much of insights or details, and it's too easy!

By Sandeep

Apr 22, 2021

The lab exercises for week 4 needs to be changed

By Alejo G

Oct 6, 2019

A lot of boilerplate code with few new concepts

By Mikołaj M

Oct 12, 2020

The course covers elementary techniques.

By Victor S

Sep 4, 2020

Useful course. Just a bit unstructured.

By Python

Jul 30, 2021

The grader keeps running out of memory

By Bojiang J

Mar 7, 2020

Content too easy and not engaging....

By Aymen M

Mar 20, 2021

The last assignment is malformed

By Navid H

Sep 15, 2019

I wish it had real assignments

By Samyak J

Aug 2, 2020

exercises are not very clear

By Paula S

Apr 6, 2020

course is a little too easy.

By Pallavi

Mar 12, 2020

It was not great and good

By Yuxuan C

Apr 12, 2020

A little bit too easy.

By Luiz C

Jun 11, 2019

not challenging enough

By Victor M

Mar 19, 2020

Contenido superficial

By Igors K

Oct 26, 2019

I wish it used TF2.

By Masoud V

Aug 21, 2019

Useful but too easy

By Ruxue P

Oct 14, 2020

Too little content

By Gerard C I

Nov 20, 2019

to much shallow

By Rob S

Sep 3, 2020

Good course

By Neshy

Nov 29, 2020

too basic

By Mohammed I A T

Sep 21, 2020

just ok

By Thomas R

Feb 8, 2021

Materials were good for someone who has taken university courses on convolutional networks, but labs were extremely poorly done. Final lab of the course was missing sections for the data generator flow method calls, and augmentation wasn't even tested for. Marker could be improved and provided code can have better sections and maybe an explaining markdown at the top rather than going back and forth. I also noticed that accuracy changed from logs.get('acc') to logs.get('accuracy') which seems to be a tensorflow version issue. I feel overall like the course has been abandoned.