Introduction to TinyML

by Rohit Sharma

This book is an effort by AI Technology & Systems to demystify the TinyML technology including market, applications, algorithms, tools and technology. the book dive deeper into the technology beyond common application and keep it light for the readers with varying background including students, hobbyists, managers, market researchers and developers. It starts with introduction to TinyML with benefits and scalability. It introduces no-code and low-code tinyML platform to develop production worthy solutions including audio wake word, visual wake word, american sign language and predictive maintenance . Last two chapters are devoted to sensor and hardware agnostic autoML and tinyML compiler technologies.

181 pages, Paperback

Published July 9, 2022

About the author

Rohit Sharma is an engineer, author and entrepreneur. He has published over 10 papers in international conferences and journals. He has contributed to electronic design automation domain for over 20 years learning, improvising and designing solutions. He is passionate about many technical topics including machine learning, analysis, characterization, and modeling. It led him to architect guna - an advanced characterization software for modern nodes. He currently works for Paripath Inc. (www.paripath.com) - a company he founded.

Reviews

[Thamina · Rating 5 out of 5]

I'm using the TinyML book to learn Tensorflow and machine learning in a practical, hands-on way. The book is a fantastic place to start learning about this technology. You can execute the programs in this book from your PC connected to inexpensive hardware from Arduino, SparkFun, and other vendors without the need for a supercomputer. To gain from this book, you don't necessarily need to be working in the tiny ML area ( 1mW, small memory, etc.); the techniques are transferable to whatever the opposite of tiny ML is. The authors' infectious passion is truly remarkable. Look them up on YouTube; they are incredibly knowledgeable about this subject and very helpful and supportive. The book favors action-oriented reading,

[Ravinder Gill · Rating 5 out of 5]

"Introduction to TinyML" by Rohit Sharma is a good read for folks with no tech skills including a 8 year old or a housewife with no time. A good approach for building smart electronics with a freely available no-code platform https://cainvas.ai-tech.systems/ that lets you create applications like person detection (you or someone else) and wake word detection (like hey google) in a matter of minutes customized for your needs. More information on free book giveaways days is at http://thetinymlbook.com/

[Madu · Rating 5 out of 5]

This book gives an in-depth view of AI&ML, while further discussing TinyML with its importance and benefits, including its application in the industrial sector.
It tells us that the purpose of TinyML is to draw the same conclusion as ML while asserting the lowest possible strength.
I like how the book dives deeper into the technology behind TinyML while keeping it light for readers with varying backgrounds. Making it easy to understand.
For anybody looking to know more about AI&ML, regardless of Educational background, this is the right book for you.

[Lyonel Mascarenhaz · Rating 5 out of 5]

Loved the non-tech and no-code approach for turning ideas into products with bunch of sensors. It is a good book for a non-technical user with any background to build smart electronics products with AI software and firmware. It's also a good reference for intermediate embedded developers, data scientists and product builders looking to build products quickly in few days for industries including smart home, smart city, smart farming, smart spaces, IIoT, industry 4.0 etc.

[Shahajun Khan · Rating 5 out of 5]

The TinyML book provides a great perspective on embedded ML, AI and the tools available for non-AI specialists who are outcome focused. And quickly looking to find how quickly, what budget and which sensor fused application can help in building the product. Highly recommended for sensor and embedded developers, users and companies.

[VLSI Designer · Rating 5 out of 5]

Author has kept this book at a level high enough to cruise through first few chapters that cover tinyML and embedded Machine Learning verticals, benefits etc. And then it gets moderately technical with sensors and electronic boards. I could not read the last chapter on tinyML compiler - way too heavy for a light reading.

Overall ⭐⭐⭐⭐⭐

[AI Reader · Rating 5 out of 5]

Excellent coverage of tinyml use cases like keyword spotting, person or object detection, sign language detection and predictive maintenance of motors and pumps.

Highly recommended for students, teachers, managers, embedded ML market researchers etc.

[Aizaz Rana · Rating 5 out of 5]

The book is very clear and helps to understand your quires. Would defiantly suggest it to others.