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Device-based Models with TensorFlow Lite に戻る による Device-based Models with TensorFlow Lite の受講者のレビューおよびフィードバック



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....



Great course - I learned a lot about how TensorFlow can be run on a wide variety of devices. I am especially interested in TensorFlow running on Raspberry Pi, Google Dev Board (Coral) and Jetson Nano.


Really informative course on tf lite for beginners like me, it has given serious thoughts about the EDGEML field and opportunities , thanks coursera and for this kind of courses.


Device-based Models with TensorFlow Lite: 1 - 25 / 89 レビュー

by Chouaib N


The topic is very interesting but the way the course is delivered is a bit disappointing. I really loved the TensorFlow in Practice specialization and the first course of the TensorFlow Data and Deployment delivered by M. Moroney. This course is not at all at their level. In addition, I'd prefer to have hands-on mandatory assignments than mere quizzes

by Ravi S


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

by Matej M


This course is good as overview - theoretical. You go through all the important topics - principles of tensorflow lite, android deployment, apple deployment, microcontrolers deployment. But unfortunately all you need is to watch. No exercises you would really need to do in order to complete the course. I mean, it is explained well but i would not call it 'course' rather 'presentation'. I dont feel i gained real competence. At least i know the theory and what are the possibilities.

by seyed r m


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

by Mo R


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

by Carlos C E


Amazing introduction course to Tensorflow models deployment on different devices.

by Qi D


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

by pervesh M


exceptionally brilliant work

by Marco A P N


Awesome. I learned a lot

by Hans-Martin D


While I like the approach to cover multiple platforms and consequently the need of availability of them to course participants, it's a pity that hand-on practice now is optional and not part of the assignments. An option maybe would be that participants choose one platform (e.g. iOS, Android, Raspbian) and than follow the course a bit more deeply and hands-on on that particular platform.

by clement l r


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.

by Martín C


Muy buen curso, las semana 2 y 3 se me hicieron más difíciles porque están orientadas a Android e iOS, de los cuales no tengo experiencia. Pero están muy bien explicadas. ¡Lo disfruté!

Very good course, weeks 2 and 3 were more difficult for me because they are oriented to Android and iOS, of which I have no experience. But they are very well explained. Enjoy it!

by Jaydeep K R


It was a great introductin to diff application fo TF models and how to deploy them acctually I enjoyed the first course more as I had already done some web development. so ya it's a useful course if you have completed TF in practise and basics of deep and machine learning this is a great way to start deploying your model using just single Tech TF.

by Nilesh G


I love the learning, before enrolling the course I wish to learn about how the models actually deploy in production but by this course I will get to learn many things with ML model deployment on Mobile devices as well as on low power devices such as Raspberry Pi and wish to learn on Micro controller as well

by Moustafa S


really good for developers simple and basic, it's also hard for a machine learning engineer to get 100% of these codes, but as for teams working on a project it takes a less effort to create a great product with this course, also loved how you didn't force us to code in other languages .

by Eleftherios M


A really interesting course by Although I would say that the course was very introductory and easy, I cannot neglect the fact that it taught me a lot of stuff on how to deploy "small" models on devices. Surely a great place to start with deploying models on devices! :)

by swaraj b


Though I am not into app development, this course gave me useful insight into how to get things done in the real world. The most useful part was the fourth week for me. Just the things I anticipated. A really great course for ML enthusiasts.

by Marvin J C I


One of the best courses I've taken. I've always worked on projects using Tensorflow models on a desktop or a laptop. This course opened new possibilities for me, and I'm now eager to develop AI applications on my smartphone and Raspberry Pi.

by Emmanuel A


Great amazing intelligent course! i learn how to apply machine learning and use TensorFlow Lite to generate the four steps to get Andoid device, IOS, Raspberry Pi, Microcontroller to perform image classification, object detection etc.

by Rick T


Great course - I learned a lot about how TensorFlow can be run on a wide variety of devices. I am especially interested in TensorFlow running on Raspberry Pi, Google Dev Board (Coral) and Jetson Nano.

by Balaji S


Really informative course on tf lite for beginners like me, it has given serious thoughts about the EDGEML field and opportunities , thanks coursera and for this kind of courses.

by Abhiram S


Excellent study material, lot of new concepts on different platforms with the same ideology of the workflow really made it a good combo of fastly taught topics but with similar connecting dots!

by Jose C


One of the most useful and exciting courses I've ever done! Especially for the information available in the last (4th) week. Very interesting material and full of practical potential!

by Pavel


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

by Gokila


Perfect course to learn about TensorflowLite and deploying tflite models on various devices. Excellent instructor and course structure. This is one that I was looking for!