Book Image

Hands-on TensorFlow Lite for Intelligent Mobile Apps [Video]

By : Juan Miguel Valverde Martinez
5 (1)
Book Image

Hands-on TensorFlow Lite for Intelligent Mobile Apps [Video]

5 (1)
By: Juan Miguel Valverde Martinez

Overview of this book

<p>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.</p> <p>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.</p> <p>By the end of the course, you will have learned to implement AI in your mobile applications with TensorFlow.</p> <p>The code bundle for this video course is available at <a style="color: #fa8d11;" href="https://github.com/PacktPublishing/Hands-on-Tensorflow-Lite-for-Intelligent-Mobile-Apps" target="blank">https://github.com/PacktPublishing/Hands-on-Tensorflow-Lite-for-Intelligent-Mobile-Apps</a></p> <h1>Style and Approach</h1> <p>You will gain an insight into solving real-life problems through Deep Learning using TensorFlow as the main tool for building models that will be later deployed on a mobile device. This course starts with a theoretical introduction and reinforces every concept by a practical code implementation. After a first simplistic example is used to understand the basics, different real-life problems in Computer Vision will deepen your knowledge by walking you through classical steps in developing an app such as identifying challenges, tackling problems, and deploying our ideas.</p>
Table of Contents (6 chapters)
Chapter 2
Developing Our First TensorFlow Model
Content Locked
Section 4
Overfitting
In this video, we will learn how to detect and deal with overfitting. - Explain what overfitting is - Detect overfitting in our model - Apply two techniques to try to deal with overfitting