Android Machine Learning with TensorFlow Lite and tf.Keras
L10 - E2E: Deploy the TFLite model to Android
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Now that you have the TensorFlow TFLite (.tflite) model, you can create an Android app to classify hand-written digits. This lesson covers how to update Gradle dependencies needed for the TensorFlow wrapper and how to create the image classifier class:
- Initialize a TFLite interpreter.
- Pre-process the input image.
- Run inference with the TFLite model via the interpreter.
- Post-process the output result for displaying in UI.
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Lessons in Android Machine Learning with TensorFlow Lite and tf.Keras
1. L0 - Course Overview
00:58
2. L1 - Google Colab Basics

03:24
3. L2 - Python Basics

03:34
4. L3 - Numpy Basics

Pro
04:10
5. L4 - Matplotlib Basics

Pro
03:18
6. L5 - Intro to Deep Learning

Pro
03:58
7. L6 - Intro to TensorFlow 2.0 and tf.Keras

Pro
03:15
8. L7 - E2E: Image Classifier - Data

Pro
05:20
9. L8 - E2E: Image Classifier - Training

Pro
06:40
10. L9 - E2E: Image Classifier - Model Conversion

Pro
05:58
11. L10 - E2E: Deploy the TFLite model to Android

Pro
06:20

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