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Retour à Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Avis et commentaires pour d'étudiants pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning par

18,161 évaluations

À propos du cours

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 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....

Meilleurs avis


8 mars 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?


13 août 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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3551 - 3575 sur 3,753 Avis pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

par Aleksandr F

9 mai 2020

Course materials are great, but there is a minor mismatch between Jupyter and Collab in versions of code and TensorFlow, as well as some comments in code, do not match the actual code below in constants. So it would be good somebody could check it through to make sure all is right.

par Alen B

6 févr. 2020

A bit bored of only doing image recognition in every TensorFlow tutorial under the sun, including this course, as if there are no other problems to solve with it. The title is so broad that frankly I was expecting a bit more for the money than just doing image recognition.

par Li P Z

19 janv. 2020

Instructor does sound job of explaining how to use TensorFlow for deep learning. Compared to Andrew's courses, much less content in the videos and exercises. I feel that much more thought and effort could have gone into this course, just look at how verbose the name is.

par alex c

4 août 2020

it would be ok if this course were free but it's not. there are technical mistakes in the multiple choice quizzes and the mandatory programming tests. some important topics are left unexplained while some are repeated unnecessarily. check the forums for more feedback.

par Nimit J

15 août 2020

Though it does give you a good introduction how to make neural networks, i felt that this course doesn't explain the Keras API library, which makes it difficult to remember and understand how things work.

I hope further courses in the specialization take care of that

par Giovanni C

29 avr. 2019

I feel there are gaps in this course. But it was still worthwhile going through the material, to reinforce certain concepts. I had the impression that the course was initially classified for beginners, and that later on that classification was modified to advanced.

par Jan B

28 avr. 2020

Rather basic, but the learner can strengthen it by broadening his reading. What I missed most is a conceptual introduction of what Tensorflow is and does.

I did not take the Deep Learning specialization before this one. Maybe that would have made a difference.

par Michael M

26 juil. 2019

Good introduction but lacks materials and practice to use after the class. Most of the materials its only referral. The trainer is good, except very shot videos and the setup on your pc are not discussed. But generally enoyed the lecture and learned a lot.

par Carlos A V P

20 juin 2019

This course is simple in comparison with the Deep Learning Especialization, However you can learn new things like training from folders and using callback for early stopping. I consider the course is of, but the course use Keras and not tensorflow directly

par Christopher N

17 sept. 2020

The graded programming assignments are a little too ambiguous for beginners. They should really spend a day or two and model their programming assignments after the way that Andrew Ng did his programming assignments in the Deep Learning Specialization.

par Edward D

11 août 2019

The homework is not designed well:1. The notebook is inconsistent with the colab env, and there are always problems here and there due to the inconsistency in tf version. 2. All 4 homeworks are similar, and it's simply a copy of the video lectures.

par Arif O

22 juil. 2019

Not at the level of the courses from Andrew Ng. I expected it to be more about TensorFlow API than machine learning concepts. It tries to do both and does not excel in any. Got some stuff out it but you can probably say that by any course.


2 juil. 2020

The course was comfortable to handle, explanations were were apt to the contents of the course, resources provided as reference were also really nice and apt, only felt that the course was a bit basic and well suited well for beginners.

par Vincent Y

20 mars 2020

A solid course, but if you have already take the deep learning specialization by Andrew Ng, there won't be too much new stuff for you. Callbacks and ImageDataGenerotor are new things for me, but I think they can be covered very quickly.

par Nitish R D

3 juin 2020

The programming assignments are vague and should be improved. The course lacks explanation content. It's more of a 'Don't question, Just follow along' tutorial. However, what is taught is presented neatly and clearly by the instructor.

par Alex E

9 nov. 2022

I found both the videos and the exercises to be a bit too disjointed. I understand that you want to break things up into bite size, but these are a little too short and, for me, caused not appreciating hoe things flow and connect.


12 oct. 2020

I understand that now Keras is inside TF 2.0 but the name of the specialisation is quite confusing. Here you learn how to use the high level API Keras not just the lower level TF. Really easy course, finished in less than a day.

par Ayush M

8 déc. 2020

Course Material not detailed enough and expected more from it. It does not contain enough variety in exercises and lacks a lot of concepts.

Anyone with good learning (and "overfitting") can complete 1 course in a day or two.

par Jay U

26 mai 2021

The material covered was very good but the options for each function should be covered. Also the labs and quizzes don't always work are the technical difficulties on submitting a lab are more work then the lab.

par Mayur K

12 août 2019

it was good but there is scope of providing more thereotical contents along with videos for the concepts beyond the scope of this course so one could get better familiar with the terms (e.g adam. cross entropy)

par Naman B

7 juin 2019

The course is very easy for anyone who has taken other courses. The course do has good and polished material but it is very small to be called as a course. Also there should be code based exams.

par José L A C

17 avr. 2020

The theoretical concepts are too basic, the sample code to learn tensorflow are quite repetitive. I think the course should be much more dense both in DNN theory and in programming to worth the money.

par victor K

7 mars 2019

A nice intro but very basic. Would have liked not using the keras api to have fewer things abstracted away. Then keras is a nice convenience once you fully understand what it is doing under the hood.

par siddharth J

27 juil. 2019

I felt the instructor is going too fast without covering the concepts of Neural networks, CNN and basics. Or maybe i need to take a supplement course for statistics and Neural networks by Andrew NG.

par Hasan E E

14 août 2019

A very good introductory course, however the algorithms working under Tensorflow was omitted heavily. Some technical background on how these algorithms work would enhance the quality of the course.