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Learner Reviews & Feedback for Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning by DeepLearning.AI

4.7
stars
16,092 ratings
3,362 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. 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

AS
Mar 8, 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?

RD
Aug 13, 2019

Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.

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3151 - 3175 of 3,379 Reviews for Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

By Siddharth A

Sep 23, 2021

good course

By Shekh T

Jun 26, 2020

Good course

By Joish J B

May 14, 2020

Loved it...

By Sajal J

Dec 9, 2019

good course

By Yue D

Jun 21, 2021

very basic

By Aniket D B

Sep 29, 2020

Very Easy.

By Chema A E

Aug 7, 2019

Very basic

By Austin E

Sep 15, 2020

Too Basic

By sunpanwei

Mar 24, 2020

very good

By Tiago B D L

Jul 23, 2020

Awesome!

By Riya S

Sep 11, 2020

like it

By MizzleNA

Jul 18, 2021

good

By Rishub C

Mar 1, 2021

nice

By Usman A

Dec 12, 2020

best

By Harsha B

Nov 22, 2020

Good

By MOURAD B

Sep 9, 2020

good

By Yasam H

Aug 22, 2020

good

By Alfonso A B

Apr 18, 2020

Easy

By Jefferson R

Sep 26, 2019

easy

By Lei M

Jun 12, 2019

入门难度

By Perry R

Apr 30, 2020

Great introductory course. The two instructors provided a nice introduction to the topics.

3 points of feedback, however. 1: The forums need to be monitored more by Coursera staff; there are many great questions (some basic) in the forums that are unfortunately never answered. 2: The grading app needs to be quality reviewed/reworked. I found myself having to consistently delete the last two unnecessary cells in the submitted notebook [something not very well documented]. Also, the error messages from a non-pass submittal are vague and not very informational. What's causing the syntax error in line xx? The syntax is perfectly fine. Code may be pefectly correct, yet fail the grader algorithm due to these quirks. 3: What is an "adam" optimizer and why am I using it? Even if it's complicated, a note about why it's out of scope and we need to use it here because of X would be very helpful for beginners.

Thank you!

By John M

May 20, 2020

The programming assignment submission system needs work. The course content is decent but very unhappy with submission system. It is very challenging to submit. I spent more time on the first two assignments figuring out how to submit than I did on the assignment themselves. I had the correct work -but the submission system stinks. Also there are issues with differing versions of python/tensorflow; I got hung up by slight changes in tensor flow api -- key values 'accuracy' versus 'acc' were challenging to debug. Ultimately I found it easier to first develop the solution on my local computer -- I would get the code running correctly. Then I would copy/paste that into the colab notebook -- but here is where I ran in to trouble -- differing versions of tensorflow. But it wasn't only me -- in fact some of the class examples had the same exact issue with key values 'acc' versus 'accuracy'.

By Michael A

Sep 1, 2020

The material is very good and comprehensive and the instructors are motivating and well-versed experts. However, for an INTRODUCTION to TensorFlow this course lacks complete introduction into TensorFlow. The very first exercise just dives into the code and does not explain with a single word how TensorFlow is structured, how the library is build, where to find important functions, what important imports are and so on and so one. You have to copy and paste the code 1:1 to get it running without understanding anything about the framework. This is a really poor approach for introducing such a powerful framework. I would have expected at least one introductory video about Tensorflow, its structure and components and what are the most important modules to work with, where you can find which function and so on (keras in tf.keras as high-level module, important functions in tf.nn to work with NN)

By Amilkar A H M

May 22, 2019

The explanations are good, but there are no graded programming assignments and this makes the course way too easy. There are only automatically graded quizes (multiple choice) and the questions are too easy. Full disclaimer: I already completed the Deep Learning specialization from deeplearning.ai so I guess that is partly why the course seems too easy from me. Still the lack of graded programming exercises is not acceptable given that this is basically a programming course. It's a shame to give this course such a low rating (3 stars) because the professor is good at explaining and the course in general has great potential, still without graded programming assignments I don't see how you can guarantee that the people with the certificate has at least a basic grasp of the programming skills required.

By Ian P

Jun 10, 2020

This is a good beginner's course, but needs a lot of polish. The presenter is very knowledgeable, but his accent is severe, and on difficult words the transcript is entirely wrong, so there's no way of knowing what he's saying. Several of the reading assignments were mis-timed, some of the reading assignments either had dead links, or it was not apparent if there used to be a point to them but there isn't one now. The assignments were buggy -- I spent more time debugging errors in the Jupyter Notebooks that were baked in than on the actual assignments. The assignments themselves were overly easy, but the hassle of debugging made the assignments hard to get through -- the "TA"s didn't answer questions in the forums.