Overview
- Learn to use algorithms to solve machine learning and data analytics problems with low power and memory usage
- Create new algorithms for real-time machine learning use cases
- Implement code with adaptive algorithms for real world use cases
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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 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
Who This Book Is For
Machine learning engineers, data scientist and architects, software engineers and architects handling edge device computation and data management.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Adaptive Machine Learning Algorithms with Python
Book Subtitle: Solve Data Analytics and Machine Learning Problems on Edge Devices
Authors: Chanchal Chatterjee
DOI: https://doi.org/10.1007/978-1-4842-8017-1
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Chanchal Chatterjee 2022
Softcover ISBN: 978-1-4842-8016-4Published: 13 March 2022
eBook ISBN: 978-1-4842-8017-1Published: 12 March 2022
Edition Number: 1
Number of Pages: XXVIII, 269
Number of Illustrations: 85 b/w illustrations
Topics: Machine Learning, Artificial Intelligence, Python