Introduction to TInyML

· AITS Inc
4.7
7 reviews
Ebook
183
Pages
Eligible
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About this ebook

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.

More information at http://thetinymlbook.com/

Ratings and reviews

4.7
7 reviews
Lyonel Mascarenhaz
September 30, 2022
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.
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Another Engineer
September 30, 2022
It is a well thought, well-written and engaging resource for users of all levels who are curious about running machine learning models on resource constrained devices including IoT devices and microcontrollers. It comes with practical demos, associated no-code steps and low-code source code with easy to follow explanations.
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TinyML Book
September 30, 2022
Good book for beginners on tinyML and embedded ML application. It covers topics from a no-code platform to tinyML compiler at a higher level. Easy to follow and understand.
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About the author

Rohit Sharma is a technocrat, author and entrepreneur. He founded two companies, published several papers in international conferences and journals and authored two best seller books on machine intelligence and VLSI cell characterization. He has contributed to ML & EDA domain for over 20 years with TI, Ansys, Cadence and Paripath learning, improvising and designing solutions. He is passionate about many technical topics including AI accelerators, AIoT, EDGE AI, machine learning, analysis, characterization, and VLSI modeling. He has architected several products including guna - an advanced characterization software for modern nodes and deepC Compiler – an open source vendor independent deep learning library, compiler and inference framework microcomputers and micro-controllers. He enjoys mentoring and speaking at technical conferences, summits and workshops. He is an adjunct professor at California Science and Technology University and works for AI Technology & Systems (ai-techsystems.com) - a company he founded.

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