更新时间：2021-06-10 19:42:11
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Mobile Landscapes in Machine Learning
Machine learning basics
Supervised learning
Unsupervised learning
Linear regression - supervised learning
TensorFlow Lite and Core ML
TensorFlow Lite
Supported platforms
TensorFlow Lite memory usage and performance
Hands-on with TensorFlow Lite
Converting SavedModel into TensorFlow Lite format
Strategies
TensorFlow Lite on Android
Downloading the APK binary
TensorFlow Lite on Android Studio
Building the TensorFlow Lite demo app from the source
Installing Bazel
Installing using Homebrew
Installing Android NDK and SDK
TensorFlow Lite on iOS
Prerequisites
Building the iOS demo app
Core ML
Core ML model conversion
Converting your own model into a Core ML model
Core ML on an iOS app
Summary
CNN Based Age and Gender Identification Using Core ML
Age gender and emotion prediction
Age prediction
Gender prediction
Convolutional Neural Networks
Finding patterns
Finding features from an image
Pooling layer
Rectified linear units
Local response normalization layer
Dropout layer
Fully connected layer
CNNs for age and gender prediction
Architecture
Training the network
Initializing the dataset
The implementation on iOS using Core ML
Applying Neural Style Transfer on Photos
Artistic neural style transfer
Background
VGG network
Layers in the VGG network
Building the applications
TensorFlow-to-Core ML conversion
iOS application
Android application
Setting up the model
Training your own model
Building the application
Setting up the camera and an image picker
References
Deep Diving into the ML Kit with Firebase
ML Kit basics
Basic feature set
Adding Firebase to our application
Face detection
Face orientation tracking
Landmarks
Classification
Implementing face detection
Face detector configuration
Running the face detector
Step one: creating a FirebaseVisionImage from the input
Using a bitmap
From media.Image
From a ByteBuffer
From a ByteArray
From a file
Step two: creating an instance of FirebaseVisionFaceDetector object
Step three: image detection
Retrieving information from detected faces
