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You're reading from  Machine Learning for Mobile

Product typeBook
Published inDec 2018
PublisherPackt
ISBN-139781788629355
Edition1st Edition
Tools
AndroidTensorFlow
Concepts
Machine Learning
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Authors (2):
Revathi Gopalakrishnan
Revathi Gopalakrishnan
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Revathi Gopalakrishnan

Revathi Gopalakrishnan is a software professional with more than 17 years of experience in the IT industry. She has worked extensively in mobile application development and has played various roles, including developer and architect, and has led various enterprise mobile enablement initiatives for large organizations. She has also worked on a host of consumer applications for various customers around the globe. She has an interest in emerging areas, and machine learning is one of them. Through this book, she has tried to bring out how machine learning can make mobile application development more interesting and super cool. Revathi resides in Chennai and enjoys her weekends with her husband and her two lovely daughters.
Read more about Revathi Gopalakrishnan

Avinash Venkateswarlu
Avinash Venkateswarlu
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Avinash Venkateswarlu

Avinash Venkateswarlu has more than 3 years' experience in IT and is currently exploring mobile machine learning. He has worked in enterprise mobile enablement projects and is interested in emerging technologies such as mobile machine learning and cryptocurrency. Venkateswarlu works in Chennai, but enjoys spending his weekends in his home town, Nellore. He likes to do farming or yoga when he is not in front of his laptop exploring emerging technologies.
Read more about Avinash Venkateswarlu

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Summary

In this chapter, we got introduced to Google's machine learning tools for Mobile and looked at the various flavors of the toolkit – TensorFlow for Mobile and TensorFlow Lite. We also explored the architecture of aTensorFlow-ML-enabled mobile application. Then we discussed the architecture and details of TensorFlow Lite and its components, and even demonstrated a simple use case for an android mobile application using TensorFlow for mobile.

In the next chapter, we will be using the TensorFlow for mobile that we discussed here to implement a classification algorithm.

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Machine Learning for Mobile
Published in: Dec 2018Publisher: PacktISBN-13: 9781788629355
© 2018 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Revathi Gopalakrishnan

Revathi Gopalakrishnan is a software professional with more than 17 years of experience in the IT industry. She has worked extensively in mobile application development and has played various roles, including developer and architect, and has led various enterprise mobile enablement initiatives for large organizations. She has also worked on a host of consumer applications for various customers around the globe. She has an interest in emerging areas, and machine learning is one of them. Through this book, she has tried to bring out how machine learning can make mobile application development more interesting and super cool. Revathi resides in Chennai and enjoys her weekends with her husband and her two lovely daughters.
Read more about Revathi Gopalakrishnan

author image
Avinash Venkateswarlu

Avinash Venkateswarlu has more than 3 years' experience in IT and is currently exploring mobile machine learning. He has worked in enterprise mobile enablement projects and is interested in emerging technologies such as mobile machine learning and cryptocurrency. Venkateswarlu works in Chennai, but enjoys spending his weekends in his home town, Nellore. He likes to do farming or yoga when he is not in front of his laptop exploring emerging technologies.
Read more about Avinash Venkateswarlu

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