課程大綱： TensorFlow Lite for iOS培訓
Introduction
Tensorflow vs Tensorflow Lite
Overview of TensorFlow Lite Features and Workflow
Recap of machine learning and deep learning concepts
How on-device low-latency inference is achieved
End-to-end model building and deployment
Preparing the Development Environment
Starting a Swift project
Adding TensorFlow to the project
Capturing an Image with a Device Camera
How camera input is captured
Overview of classes and methods
Running inference on a frame (performing image classification)
Creating an App for Object Detection
Selecting a TensorFlow Model
Converting the TensorFlow Model
Loading the TensorFlow Model onto a Mobile Device
Loading a Pre-trained TensorFlow Model
Creating an App for Image Classification
Selecting a TensorFlow Model
Converting the TensorFlow Model
Loading the TensorFlow Model onto a Mobile Device
Loading a Pre-trained TensorFlow Model
Customizing the Model and Data
Pre-processing a dataset
Setting the hyperparameters
Optimizing the TensorFlow Model
Measuring performance against a benchmark
Measuring accuracy
Retraining a TensorFlow model
Exploring Alternative Models
Choosing a different model
Training a model to recognize new classes (transfer learning)
Obtaining training images for new labels
Deploying the AI Enabled iOS App
Performing image classification in the field
Troubleshooting
Summary and Conclusion
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