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You're reading from  Machine Learning for Mobile

Product typeBook
Published inDec 2018
PublisherPackt
ISBN-139781788629355
Edition1st Edition
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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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An introduction to TensorFlow


TensorFlow is a tool to implement machine learning developed by Google, and was open sourced in 2015. It is a product that can be installed on desktops and can be used to create machine learning models. Once the model has been built and trained on the desktop, the developer can transfer these models to mobile devices and start using them to predict results in mobile applications by integrating them into iOS and Android mobile applications. There are currently two flavors of TensorFlow available for implementing machine learning solutions on mobile and embedded devices:

  • Mobile devices: TensorFlow for Mobile
  • Mobile and Embedded devices: TensorFlow Lite 

The following table will help you to understand the key differences between TensorFlow for mobile and TensorFlow Lite:

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Machine Learning for Mobile
Published in: Dec 2018Publisher: PacktISBN-13: 9781788629355

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

TensorFlow for Mobile

TensorFlow Lite

Designed to work with larger devices.

Designed to work with really small devices.

Binary is optimized for mobile.

Binary is really very small in size optimized for...