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1
Introduction
2
What is TensorFlow Lite
3
Benefits
4
Early Access Program
5
Sample App
6
Dependencies
7
Classes
8
Initialization
9
Interpreter API
10
Dependency
11
move model to GPU
12
performance
13
languages support
14
Java support
15
API delegate
16
Optimization
17
Language support
Description:
Explore TensorFlow Lite integration in Android using Google Play services in this 46-minute talk by He Jiang. Discover how to run ML models without statically bundling TensorFlow Lite libraries, reducing app size and improving performance. Learn about the Early Access Program, sample app implementation, dependencies, classes, initialization, and Interpreter API. Gain insights on moving models to GPU, performance optimization, language support including Java, and API delegates. Understand the benefits and practical applications of TensorFlow Lite in Android development for efficient machine learning deployment.

TensorFlow Lite in Android with Google Play Services

TensorFlow
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