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New Kind of Machine Learning–Cellular Automata Model

By: (Author) Adip Dutta , (Author) Dipanwita Roy Chowdhury , (Author) Parimal Pal Chaudhuri , (Author) Raju Hazari , (Author) Somshubhro Pal Choudhury

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Ksh 9,000.00

Format: Hardback or Cased Book

ISBN-10: 9819615003

ISBN-13: 9789819615001

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Apr 26th, 2025

Print length: 395 Pages

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This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver e?cient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions e?ectively. The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another signi?cant application is in multi-language Sentiment Analysis, where the model analyzes text in ?ve languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models. CAML uses CA rules for Unicode character modeling, o?ering a transparent, interpretable prediction algorithm. Overall, CAML aims to drive industrial and societal applications of CA, with an emphasis on transparent results and e?cient hardware design through CA’s regular, modular, and scalable structure.

This book introduces the CAML model, a novel integration of Cellular Automata (CA) and Machine Learning (ML), designed to deliver e?cient computation with minimal training data and low computing resources. CAML operates through two key perspectives: one where CA is enhanced by ML to handle complex non-linear evolution, and another where CA strengthens ML by leveraging linear CA evolution to process linear functions e?ectively.

The book focuses on real-world applications of CA, such as in Computational Biology, where CAML models protein chains to predict mutations linked to human diseases, using carefully designed CA rule sequences for each amino acid. Another signi?cant application is in multi-language Sentiment Analysis, where the model analyzes text in ?ve languages (Hindi, Arabic, English, Greek, and Georgian), without relying on pre-trained language models.

CAML uses CA rules for Unicode character modeling, o?ering a transparent, interpretable prediction algorithm.

Overall, CAML aims to drive industrial and societal applications of CA, with an emphasis on transparent results and e?cient hardware design through CA’s regular, modular, and scalable structure.


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