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Adaptive Machine Learning Algorithms with Python = Solve Data Analytics and Machine Learning Problems on Edge Devices /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Adaptive Machine Learning Algorithms with Python/ by Chanchal Chatterjee.
Reminder of title:	Solve Data Analytics and Machine Learning Problems on Edge Devices /
Author:	Chatterjee, Chanchal.
Description:	XXVIII, 269 p. 85 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-1-4842-8017-1
ISBN:	9781484280171

Adaptive Machine Learning Algorithms with Python = Solve Data Analytics and Machine Learning Problems on Edge Devices /
Chatterjee, Chanchal.

Adaptive Machine Learning Algorithms with PythonSolve Data Analytics and Machine Learning Problems on Edge Devices /[electronic resource] :by Chanchal Chatterjee. - 1st ed. 2022. - XXVIII, 269 p. 85 illus.online resource.

Chapter 1. Introducing Data Representation Features -- Chapter 2. General Theories and Notations -- Chapter 3. Square Root and Inverse Square Root -- Chapter 4. First Principal Eigenvector -- Chapter 5. Principal and Minor Eigenvectors -- Chapter 6. Accelerated Computation eigenvectors -- Chapter 7. Generalized Eigenvectors -- Chapter 8. Real – World Applications Linear Algorithms.

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. You will: Apply adaptive algorithms to practical applications and examples Understand the relevant data representation features and computational models for time-varying multi-dimensional data Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data Speed up your algorithms and put them to use on real-world stationary and non-stationary data Master the applications of adaptive algorithms on critical edge device computation applications.

ISBN: 9781484280171

Standard No.: 10.1007/978-1-4842-8017-1doiSubjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5-.7

Dewey Class. No.: 006.31

Adaptive Machine Learning Algorithms with Python = Solve Data Analytics and Machine Learning Problems on Edge Devices /
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