Difference between revisions of "AI & Machine Learning"

From Miscellany
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==TinyML==
 
==TinyML==
<q>... [a] subfield of machine learning including algorithms, techniques and applications for resource constrained hardware capable of running small software applications. ... intended for small microcontroller units and embedded systems.</q>
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<q>Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.</q>
:: --Rohit Sharma in [https://www.amazon.com/dp/B0B662D7ZW Introduction to TinyML]
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:: --[https://tinyml.org The TinyML Foundation]
  
 
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Revision as of 15:07, 23 October 2022

this page is under construction

Definitions

Artificial Intelligence (AI)

the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, learning, decision-making, and natural language processing

-- IEEE.org

Machine Learning (ML)

In general, ML is the use of computer algorithms that can learn and adapt from processing digital data.

--Rohit Sharma in Introduction to TinyML

Deep Learning (DL)

[a subfield of ML] that relies heavily on neural networks to process data and produce results

--Rohit Sharma in Introduction to TinyML

TinyML

Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.

--The TinyML Foundation


References