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Voltar para Browser-based Models with TensorFlow.js

Comentários e feedback de alunos de Browser-based Models with TensorFlow.js da instituição deeplearning.ai

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Sobre o curso

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....

Melhores avaliações

JG

19 de dez de 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!

EJ

17 de mar de 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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126 — 150 de 196 Avaliações para o Browser-based Models with TensorFlow.js

por Ravinder A

20 de mar de 2020

wonderful...

por Muhammad T

23 de abr de 2021

good course

por Jamie N

24 de mar de 2020

Fun course!

por Bintang F E

27 de mai de 2021

Awesome!!!

por Ibrahim A

12 de mai de 2021

very good

por Kamlesh C

24 de jul de 2020

Thank you

por Ming G

9 de mar de 2020

Very good

por aravind

3 de fev de 2020

Excellent

por Prem S M

13 de set de 2021

Amazing!

por kingjs

7 de abr de 2022

helpful

por Muhammad N J R M

22 de mai de 2021

kerenen

por Levina A

10 de mai de 2021

So cool

por Makafui A

9 de jan de 2020

Awesome

por Sabrina M U

4 de mai de 2021

GREAT!

por mochammad g r

21 de abr de 2021

Thanks

por Ed C C C

11 de ago de 2020

Great!

por Indria A

4 de mai de 2021

COOL!

por Egi R T

15 de jul de 2022

Good

por Syamsul T P A

28 de abr de 2022

good

por Ahmad H N

22 de abr de 2021

Good

por Roberto

22 de mai de 2021

ty

por Lim H H

19 de set de 2020

The audio volume of the videos in this course is extremely low (compared to 5 courses I took by Andrew Ng) and make it very hard to listen. I have to max out my speaker to listen to them.

Also, the version requirement tensorflow for the Week 3 assignment needs to be emphasis to avoid wasting everyone's valuable time. Also, many on the forum were suggesting tensorflowjs = 1.2.9 (which incompatible with tensorflow 2.0.0) is the key to complete the assignment misleaded me and wasted many hours.

por Matej M

15 de fev de 2021

The course is easy to follow up and is very easy to pass the graded exercises as you only need to copy-paste code from examples. However to understand what you are doing you have to have already knowledge of tensorflow as such. This course is great if you want to make browse-based ML applications and need few (basic) examples.

However, the discussion forum is lacking qualified tutors very much. There are tons of questions without answer. This is something deeplearning.ai should focus on.

por Michael M

29 de dez de 2019

The course is exciting and very practical. Regardless of the last assignment in course 4 which is not very clear on what is required and whether the samples you are providing are correct, as some of us have low resolution webcams and are dark from Africa. As compared to the Tensorflow in practice, the deep learning team is building momentum. Overall, good work guys. Excited to go to the next course.

por Aladdin M

16 de abr de 2020

the course was really good and gave me a good start to tensorflow js but there were some points didn't be cleared much like what is the drawbacks of transfer learning as 2 models not only one and what is actually done when we load a model from online json file.