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.
Этот курс входит в специализацию ''Специализация TensorFlow: Data and Deployment'
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Об этом курсе
Basic understanding of Kotlin and/or Swift
Чему вы научитесь
Prepare models for battery-operated devices
Execute models on Android and iOS platforms
Deploy models on embedded systems like Raspberry Pi and microcontrollers
Приобретаемые навыки
- TensorFlow Lite
- Mathematical Optimization
- Machine Learning
- Tensorflow
- Object Detection
Basic understanding of Kotlin and/or Swift
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Программа курса: что вы изучите
Device-based models with TensorFlow Lite
Running a TF model in an Android App
Building the TensorFLow model on IOS
TensorFlow Lite on devices
Рецензии
- 5 stars77,23 %
- 4 stars16,63 %
- 3 stars4,55 %
- 2 stars0,87 %
- 1 star0,70 %
Лучшие отзывы о курсе DEVICE-BASED MODELS WITH TENSORFLOW LITE
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.
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!
Quite good course. It gives an opportunity for individuals to utilize tensor flow in day to day devices which makes it more appealing. Thanks for developing this course.
Good introduction into getting TensorFlow models up and running on different platforms from microcontrollers, raspberry PI through to IOS and Android
Специализация TensorFlow: Data and Deployment: общие сведения

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