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Avis et commentaires pour d'étudiants pour Browser-based Models with TensorFlow.js par

897 évaluations

À propos du cours

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this first course, you’ll train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam. This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Meilleurs avis


19 déc. 2020

Excellent course!!! It is actually a milestone for people like me who have trained models in Jupyter notebooks, but Tensorflow JS is actually a great way for the models to become 'alive'! Thanks!


17 mars 2021

This course is very practical and interesting.

I enjoyed the excitement I got along the way.

It was modeled to make you pass as long as you want to pass.

Thank you Laurence and Andrew.

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176 - 196 sur 196 Avis pour Browser-based Models with TensorFlow.js

par Ignacio R L

4 mai 2020

Good course to use Tensorflow in your browser

par Himanshu Y

31 juil. 2021

Was insightful and fun, Thanks.

par Jefferson R

18 janv. 2021

Faltó un poco mas de contenido

par Dan R

3 juin 2020

very amusing lectures!

par Taehun K

2 janv. 2020


par stephane d

12 juil. 2020

Laurence Moronay is really a great teacher and the course is very interesting and pleasant.

I Have removed 2 stars for the time wasted trying to make the examples and exercises provided with the course work :

=> Mobilenet Model version not compliant with the grader

=> A lot of WebGL issues (solved by setting backend parameter to "cpu")

Suggestion : report these issues during training to avoid hours spent on the forum

We can see people who already had these problems months ago and nothing is done to improve things

par Francesco B

2 nov. 2020

The course is good and interesting. It gives an overall idea on how to embed TF models in js. As in other courses of this specialisation, it is not an in-depth course but rather a fast-forward one: in my opinion this is good if you are not interested that much in these topics, not enough if you want to go deep. Nevertheless, contents are still comprehensible and concepts quite clearly explained. However, one might find more than one difficulties when trying to implement something by themselves.

par Tryggvi E

12 avr. 2020

Mildly interesting to see this work can be done in JS, but from my viewpoint: Why? I already can do it in Python... I am only stepping through this course on my way to the third and fourth courses in this specialization.

par Chris K

18 avr. 2020

Quizzes are based on syntax and spelling, which feels like a waste of time. Questions should be more about concepts. Examples are pretty basic.

par Igor M

3 janv. 2020

Too basic. All exercises are copy paste from the shown examples. All 4 weeks you can complete in just 1.

par Simon O

19 janv. 2020

Not as good as previous deep learning courses. The exams could have been a bit harder.

par Jeremy O C M

27 avr. 2021

the submission grader for all of the weeks need to be updated.

par check l

4 avr. 2021

Explain the accuracy requirements for the assignments

par Abungu B O

1 nov. 2020

ohh the last assignment on rock paper and scissors

par Stephan S

23 déc. 2019

A lot of coding and only a few ML/AI concepts.

par Jochen R

17 déc. 2019

it is very exhausting to pass the tests due to hardware and software prblems, though the programming is very easy

par Vitalii K

16 déc. 2020

A lot of explanation of obvious things. Also, excercises are low quality, with Week 3 and 4 quite hard to pass because of technical issues. Week 3 - need specific versions of the libraries, which are not provided, without which "the model is invalid". Week 4 - quite hard to collect training samples for the model to reach required accuracy, since the app crashes after ~200 examples and wipes them out - you have to start again.

par Yoni K

25 juin 2021

So many technical issues!

90% of the time I dealt with technical issues such as make the web server run my code.

The course itself was very short and easy.

par Musalula S

2 mai 2020

The course content is very good but the instructions on how to install Tensorflow 2.0 and Tensorflow.js in python 3 are not clear.

par Indira P

12 mai 2021

The assignment system was sooo frustrating and wasting my time. Please fix it..

par szymelfenig

11 oct. 2020

week 4 submission....