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Behavior Analysis with Machine Learning Using R

Af: Enrique Garcia Ceja Engelsk Paperback

Behavior Analysis with Machine Learning Using R

Af: Enrique Garcia Ceja Engelsk Paperback
Tjek vores konkurrenters priser

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial.

Features:

  • Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on.

  • Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources.

  • Use unsupervised learning algorithms to discover criminal behavioral patterns.

  • Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images.

  • Evaluate the performance of your models in traditional and multi-user settings.

  • Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors.

This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Tjek vores konkurrenters priser
Normalpris
kr 488
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial.

Features:

  • Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on.

  • Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources.

  • Use unsupervised learning algorithms to discover criminal behavioral patterns.

  • Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images.

  • Evaluate the performance of your models in traditional and multi-user settings.

  • Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors.

This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Produktdetaljer
Sprog: Engelsk
Sider: 400
ISBN-13: 9781032067056
Indbinding: Paperback
Udgave:
ISBN-10: 1032067055
Udg. Dato: 29 jan 2024
Længde: 23mm
Bredde: 233mm
Højde: 155mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 29 jan 2024
Forfatter(e): Enrique Garcia Ceja
Forfatter(e) Enrique Garcia Ceja


Kategori Automatisk styrings- & reguleringsteknik


ISBN-13 9781032067056


Sprog Engelsk


Indbinding Paperback


Sider 400


Udgave


Længde 23mm


Bredde 233mm


Højde 155mm


Udg. Dato 29 jan 2024


Oplagsdato 29 jan 2024


Forlag Taylor & Francis Ltd

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