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

3.5 (2 reviews total)
By Juan Miguel Valverde Martinez
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About this video

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

Style and Approach

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.

Publication date:
March 2018
2 hours 43 minutes

About the Author

  • Juan Miguel Valverde Martinez

    Juan Miguel Valverde Martinez is a Deep Learning, Computer Vision and Tensorflow enthusiast, with an MSc in IT and Cognition from the University of Copenhagen. His main interests are Computer Vision and Medical Image Analysis, and he has recently been more interested in Adversarial Training and Natural Language Processing. In his free time, he likes to read papers and research.

    In addition to Computer Science, he also enjoys learning languages and cooking, especially Mediterranean and Asian dishes.

    Browse publications by this author

Latest Reviews

(2 reviews total)
Very good intro. I also like the video.
I expected much more from it, e.g the hand gesture project used background subtraction which posed the problem of static background which is unreal in real life. Yes, I can understand that other methods might be a little lengthy but I expected something more practical

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