Tutorial on Machine Learning for Intelligent Mobile User Interfaces using Keras at MobileHCI ’18

Tutorial Abstract: High-level APIs such as Keras facilitate the development of deep learning models through a simple interface and enable users to train neural networks within a few lines of code. Building on top of TensorFlow, trained models can be exported and run efficiently on mobile devices. This enables a wide range of opportunities for researchers and developers. In this tutorial, we teach attendees three basic steps to run neural networks on a mobile phone: Firstly, we will teach how to develop neural network architectures and train them with Keras based on the TensorFlow backend. Secondly, we show the process to run the trained models on a mobile phone. In the final part, we demonstrate how to perform human activity recognition using existing mobile device sensor datasets.

InstructorsHuy Viet Le, Sven Mayer, Abdallah El Ali, Niels Henze

Date: 3rd September 2018

Location: MobileHCI ’18, Barcelona, Spain (https://mobilehci.acm.org)

Topics that we will cover:

  • Introduction
  • Overview of machine learning and recent advances in the field
  • Hands-on introduction to Jupyter and Keras
  • Discussion of performance metrics for classification and regression
  • Bringing TensorFlow models to Android devices
  • Human Activity Recognition research and supervised learning on time series data
  • Hands-on training of human activity recognition classifier
  • Deploying the classifier to Android devices
  • Wrap-Up and Q&A

 

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