We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Machine Learning on the Edge: Android NN Api & TFlow

Formale Metadaten

Titel
Machine Learning on the Edge: Android NN Api & TFlow
Untertitel
A short tour covering machine learning on mobile / small devices
Alternativer Titel
Neural Networks on your mobile phone: Diving into the NN Api
Serientitel
Anzahl der Teile
90
Autor
Lizenz
CC-Namensnennung 3.0 Unported:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen.
Identifikatoren
Herausgeber
Erscheinungsjahr
Sprache

Inhaltliche Metadaten

Fachgebiet
Genre
Abstract
Machine learning, deep learning are THE hot topics these days. Most machine learning tasks are handled on fast&expensive dedicated hardware. Complex structures based on larger models with lots of training data are in dare need of the any GPU cycles and local memory available. Yet, is already practical to run (infer) already trained NN models on your mobile today. The Neural Network API (NN API) - introduced for Android 8.1 - is available on some handsets already and a major step towards a new breed of applications and use cases. This talk provides an overview into the current state of machine learning/deep learning and crosses the bridge to some typical uses cases, which can be run on the mobile handset. Dedicated NN hardware will shift the scenario even further. Highly specialized and dedicated NN hardware will allow for more and more complex local models running on the handset - without the need to call back home to let the model run in the cloud.