PACKT HANDS ON TENSORFLOW LITE FOR INTELLIGENT MOBILE APPS TUTORIAL
General:Training
Size: 913.18 MB
Description
University of OXford & University of camBRiDGE
is a collective term for characteristics that the two institutions share
Hands-on TensorFlow Lite for Intelligent Mobile Apps
Published by: Packt
Mar 2018
Lecture Size: 20x50
Length: +2 hrs
Lecture Date: 10/2018
Lecture Link: https://www.safaribooksonline.com/
https://www.packtpub.com: | Apply Machine Learning models in real-time in mobile devices with
| the new and powerful TensorFlow Lite
|
| About This Video
|
| Understand the main theory behind Deep Learning and how to
| apply it in practice
| Gain practical knowledge by coding TensorFlow models to solve
| real-life problems such as gesture or voice recognition
| Learn how to deploy TensorFlow models on mobile devices
|
| In Detail
|
| This complete guide will teach you how to build and deploy Machine
| Learning models on your mobile device with TensorFlow Lite. You
| will understand the core architecture of TensorFlow Lite and the
| inbuilt models that have been optimized for mobiles
|
| You will learn to implement smart data-intensive behavior, fast
| predictive algorithms, and efficient networking capabilities with
| TensorFlow Lite. You will master the TensorFlow Lite Converter
| which converts models to the TensorFlow Lite file format. This
| course will teach you how to solve real-life problems related to
| Artificial Intelligence such as image, text, and voice
| recognition by developing models in TensorFlow to make your
| applications really smart. You will understand what Machine
| Learning can do for you and your mobile applications in the most
| efficient way. With the capabilities of TensorFlow Lite you will
| learn to improve the performance of your mobile application and
| make it smart
|
| By the end of the course, you will have learned to implement AI in
| your mobile applications with TensorFlow
|
| The code bundle for this video course is available at
| https://github.com/PacktPublishing/Hands-on-Tensorflow-Lite-for
| Intelligent-Mobile-Apps
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