Adaptive Machine Learning Algorithms with Python

Solve Data Analytics and Machine Learning Problems on Edge Devices

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Éditeur :

Apress


Paru le : 2022-03-12



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Description



Learn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use.
Authors Chanchal Chatterjee and Vwani P. Roychowdhury begin by introducing a common framework for creating adaptive algorithms, and demonstrating how to use it to address various streaming data issues. Examples range from using matrix functions to solve machine learning and data analysis problems to more critical edge computation problems. They handle time-varying, non-stationary data with minimal compute, memory, latency, and bandwidth. 
Upon finishing this book, you will have a solid understanding of how to solve adaptive machine learning and data analytics problems and be able to derive new algorithms for your own use cases. You will also come away with solutions to high volume time-varying data with high dimensionality in a low compute, low latency environment.
What You Will Learn
Apply adaptive algorithms to practical applications and examplesUnderstand the relevant data representation features and computational models for time-varying multi-dimensional dataDerive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real dataSpeed up your algorithms and put them to use on real-world stationary and non-stationary dataMaster the applications of adaptive algorithms on critical edge device computation applications

Who This Book Is For

Machine learning engineers, data scientist and architects, software engineers and architects handling edge device computation and data management.
Pages
269 pages
Collection
n.c
Parution
2022-03-12
Marque
Apress
EAN papier
9781484280164
EAN PDF
9781484280171

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
9718 Ko
Prix
46,34 €
EAN EPUB
9781484280171

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
20480 Ko
Prix
46,34 €

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