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.
Este curso forma parte de Programa especializado: TensorFlow: Data and Deployment
Ofrecido Por


Acerca de este Curso
Basic understanding of Kotlin and/or Swift
Qué aprenderás
Prepare models for battery-operated devices
Execute models on Android and iOS platforms
Deploy models on embedded systems like Raspberry Pi and microcontrollers
Habilidades que obtendrás
- TensorFlow Lite
- Mathematical Optimization
- Machine Learning
- Tensorflow
- Object Detection
Basic understanding of Kotlin and/or Swift
Ofrecido por
Programa - Qué aprenderás en este curso
Device-based models with TensorFlow Lite
Running a TF model in an Android App
Building the TensorFLow model on IOS
TensorFlow Lite on devices
Reseñas
- 5 stars77,23 %
- 4 stars16,63 %
- 3 stars4,55 %
- 2 stars0,87 %
- 1 star0,70 %
Principales reseñas sobre DEVICE-BASED MODELS WITH TENSORFLOW LITE
Really informative course on tf lite for beginners like me, it has given serious thoughts about the EDGEML field and opportunities , thanks coursera and deeplearning.ai for this kind of courses.
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!
Same as the previous course of this specialization:
The assignments are not very challenging. But the exercises are really cool!!
Great course for ML on Microcontroller and Mobile Devices, got a strong foundation to learn more in this field of Edge ML with TensorFlow Lite.
Acerca de Programa especializado: TensorFlow: Data and Deployment

Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
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