Difference between revisions of "AI & Machine Learning"

From Miscellany
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* [https://tinymlbook.com/ TinyML book] homepage (with videos & large sample PDF)
 
* [https://tinymlbook.com/ TinyML book] homepage (with videos & large sample PDF)
 
** [https://www.amazon.com/TinyML-Learning-TensorFlow-Ultra-Low-Power-Microcontrollers/dp/1492052043 TinyML] book on Amazon
 
** [https://www.amazon.com/TinyML-Learning-TensorFlow-Ultra-Low-Power-Microcontrollers/dp/1492052043 TinyML] book on Amazon
* [https://spectrum.ieee.org/number-representation New thoughts on number representation for ML]
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* [https://spectrum.ieee.org/number-representation New thoughts on number representation for ML] - article
 
* [https://www.amazon.com/TinyML-Cookbook-artificial-intelligence-ultra-low-power/dp/180181497X TinyML Cookbook]
 
* [https://www.amazon.com/TinyML-Cookbook-artificial-intelligence-ultra-low-power/dp/180181497X TinyML Cookbook]
 
* [https://www.amazon.com/dp/B0B662D7ZW Introduction to TinyML]
 
* [https://www.amazon.com/dp/B0B662D7ZW Introduction to TinyML]

Revision as of 14:33, 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

... [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.

--Rohit Sharma in Introduction to TinyML


References