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Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices
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Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices
Adaptive Machine Learning Algorithms with Python: Solve Data Analytics and Machine Learning Problems on Edge Devices
物品 #: 67893645

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

88% of respondents would recommend this to a friend

物品 #: 67893645

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HKD 625

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What Stands Out

Edge Computing Focus
Utilizes adaptive algorithms specifically designed for edge devices, enabling efficient data processing and real-time analytics where conventional methods fall short.
Practical Implementation
Offers hands-on guidance through Python examples, ensuring users can apply complex machine learning concepts directly to real-world data problems.
Versatile Solutions
Addresses a broad range of data analytics challenges, making it suitable for data scientists, engineers, and developers looking to enhance their machine learning skill set.

產品詳情

Solve ML problems on edge devices with Python using adaptive machine learning algorithms. Buy the 1st edition from Ubuy's 香港.
  • 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 LearnApply 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 applicationsWho This Book Is ForMachine learning engineers, data scientist and architects, software engineers and architects handling edge device computation and data management.
Publisher Apress
Publication date March 13, 2022
Edition First Edition
Language English
Print length 297 pages
ISBN-10 1484280164
ISBN-13 978-1484280164
Item Weight 1 pounds (450 grams)
Dimensions 6.1 x 0.68 x 9.25 inches (15.5 x 1.7 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists seeking to implement machine learning solutions on edge devices using Python.

  • Developers

    Great for developers who need to integrate adaptive machine learning algorithms into software applications effectively.

  • Tech Enthusiasts

    Perfect for tech enthusiasts wanting to deepen their understanding of machine learning applications on edge computing.

Not Suitable For
  • Beginners in Python

    Not suitable for those new to Python or programming, as a foundational knowledge is essential for understanding.

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Intelligence & Semantics Editorial Review

This book is a comprehensive guide on using adaptive machine learning algorithms with Python to solve data analytics and machine learning problems on edge devices. It provides a step-by-step approach to understanding and implementing adaptive machine learning algorithms, with a focus on practical applications. The book covers a wide range of topics, including data preprocessing, feature selection, model training, and evaluation. The author provides clear explanations, code examples, and real-world case studies to help readers learn and apply the algorithms effectively. Overall, this book is a valuable resource for anyone interested in leveraging the power of adaptive machine learning algorithms on edge devices.

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優點

  • Comprehensive guide on using adaptive machine learning algorithms with Python
  • Includes step-by-step approach and practical applications
  • Clear explanations and code examples provided
  • Real-world case studies included

缺點

  • May not be suitable for beginners with no prior knowledge of machine learning

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HKD 386

HKD 625

現在訂購，約可在下列時間收貨： 星期五, 十一月 06

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