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Voltar para Device-based Models with TensorFlow Lite

Comentários e feedback de alunos de Device-based Models with TensorFlow Lite da instituição

100 classificações
22 avaliações

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. This second course teaches you how to run your machine learning models in mobile applications. You’ll learn how to prepare models for a lower-powered, battery-operated devices, then execute models on both Android and iOS platforms. Finally, you’ll explore how to deploy on embedded systems using TensorFlow on Raspberry Pi and microcontrollers. 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


Mar 19, 2020

Same as the previous course of this specialization:\n\nThe assignments are not very challenging. But the exercises are really cool!!


Feb 05, 2020

excellent course with practical examples on using TensorFlow Lite on Raspberry, Android and iOS

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1 — 23 de {totalReviews} Avaliações para o Device-based Models with TensorFlow Lite

por seyed r m

Feb 05, 2020

excellent course with practical examples on using TensorFlow Lite on Raspberry, Android and iOS

por Mo R

Jan 05, 2020

A great course to learn how to implement any Deep Learning models on edge devices.

por Carlos C E

Feb 18, 2020

Amazing introduction course to Tensorflow models deployment on different devices.

por Qi D

Feb 10, 2020

great!!!exactly what i want for my undergrad thesis application

por pervesh M

Feb 06, 2020

exceptionally brilliant work

por Marco A P N

Jan 17, 2020

Awesome. I learned a lot

por Ravi S

Feb 15, 2020

Just one recommendation, may be an exercise on a NLP Model deployment (Text or audio) could have been added rather than all 3 examples of computer vision

por clement l r

Mar 06, 2020

This course is an excellent introduction to TFlite and how Tensorflow can be deployed on mobile and edge device like raspberry pi. From all the Tensorflow specialization so far I found it the most difficult as it requires advanced knowledge on app development, even though not mandatory to validate the course. It shows well however the value and use case of bringing tensorflow to those device. I think that one of the greatest difficulty with TFlite is that we are switching to "3rd party" ecosystem, that requires important effort to convert interfaces of the different worlds, aka tensorflow "python" ecosystem to Android/IOS ecosystems. This is anyway great material that bring incredible value to path the way for inferencing at the edge.

por Pavel K

Mar 24, 2020

The material is really interesting. The ability to try out trained models on your own device is awesome! However there are some errors in tasks, Week 4 seems a little bit raw

por Fabrice L

Mar 19, 2020

Same as the previous course of this specialization:

The assignments are not very challenging. But the exercises are really cool!!

por Balaji B

Mar 23, 2020

Nice Course! The course contents are awesome eager to use this in all my learning in future

por AasaiAlangaram

Mar 06, 2020

Very Useful course for me. I enjoyed go through first 3 week materials. Then comes the week 4 which is my favorite part because in which we learn about using tensorflow-lite in edge computing devices like raspberry pi, sparkfun edge modele. Expecting Much more from like this one.

por Igor M

Jan 07, 2020

This course provided useful information on device specific implementation of TFlite. With an interesting optional assignments, though the assignments are the same with just some small differences in implementation.

por Michael

Jan 12, 2020

Great course, very practical in the real world. It also balances and accommodates developers on what devices you have available. Looking forward to the next course

por Bourgoin C

Jan 17, 2020

Interesting course on how to use Tensorflow Lite on mobile phone or raspberry. More projects & sometimes more explanations about configuration would be necessary.

por carlos r l

Mar 09, 2020

The course is straightforward and very useful. I learned many new concepts regarding Tensorflow Lite in devices.

por Christian J R F

Feb 09, 2020

Great course, a bit short of content and exercises but it was well designed.

por Ihor M

Mar 11, 2020

It could be more coding exercises, but as for the general info it's great.

por Jinxiang R

Feb 26, 2020

good demo for IOS and Android apps use tensorflow lite

por Gaurav K

Mar 18, 2020

Difficult for a python user

por Desiré D W

Dec 25, 2019

Great course, content and instructor, but the assignment had some issues.

I submitted over 10 times without any feedback other then 'Grader Malfunction'. Also, all those times, the test cells in the notebook (put together by the instructors) ran smoothly, leaving my in the dark how to fix it. Was a bit of a frustrating experience.

Other than that, great content, very condense, very valuable to know how to deploy models on apps or small machines. This course inspired me to learn more about robotics - to apply ML on physical projects.

por Nick S

Mar 12, 2020

I am a bit disappointed by this course. I have much difficulty to pass the exercise on week 1 because of a cryptic module error. Unfortunately, no support the team was provided to solve the issue. The forum is almost not active at all.

por Ali E

Mar 29, 2020

I checked this course for free. The subject matter is very interesting and I wished it had reasonable support (mentor response) and portability (meaning running on my own computer). Unfortunately, while Mr. Moroney does an excellent job at presenting the class, the exercises are unstable, crash for reasons other than my own code and there is ABSOLUTELY ZERO tech support! The discussion forum is an empty echo chamber. As usual, one wastes time trying to debug stupid python routine crashes that have nothing to do with the actual problem at hand. Cousera, you cannot charge for this class!