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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung TensorFlow: Data and Deployment
von


Über diesen Kurs
Basic understanding of Kotlin and/or Swift
Was Sie lernen werden
Prepare models for battery-operated devices
Execute models on Android and iOS platforms
Deploy models on embedded systems like Raspberry Pi and microcontrollers
Kompetenzen, die Sie erwerben
- TensorFlow Lite
- Mathematical Optimization
- Machine Learning
- Tensorflow
- Object Detection
Basic understanding of Kotlin and/or Swift
Lehrplan - Was Sie in diesem Kurs lernen werden
Device-based models with TensorFlow Lite
Running a TF model in an Android App
Building the TensorFLow model on IOS
TensorFlow Lite on devices
Bewertungen
- 5 stars77,23 %
- 4 stars16,63 %
- 3 stars4,55 %
- 2 stars0,87 %
- 1 star0,70 %
Top-Bewertungen von DEVICE-BASED MODELS WITH TENSORFLOW LITE
I am glad I did this course to learn about exciting options to run Tensorflow on a variety of devices. I am thinking about Raspberry Pi and iOS devices in particular
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!
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.
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
Über den Spezialisierung TensorFlow: Data and Deployment

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