Apress.-.Beginning.Anomaly.Detection.Using.Python.Based.Deep.Learning.2019.Retail.EPUB.eBook-BitBook
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NFO
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| P R.E S E N T S . |
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| Beginning Anomaly Detection Using Python-Based Deep Learning |
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| DATE: 21-03-2020 SIZE: 42.13 MB DISKS: 1x50.00MB PAGES: n/a |
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| PUBLISHER: Apress GENRE: |
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| AUTHOR: Sridhar Alla, Suman Kalyan Adari |
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| FORMAT: EPUB PROTECTION: DRM EDITION: n/a |
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| URL: https://is.gd/K1szhR |
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| LANGUAGE: English ISBN: 9781484251775 |
: :
: Utilize this easy-to-follow beginner's guide to understand how deep :
: learning can be applied to the task of anomaly detection. Using Keras and :
: PyTorch in Python, the book focuses on how various deep learning models ca :
: be applied to semi-supervised and unsupervised anomaly detection tasks. :
: This book begins with an explanation of what anomaly detection is, what it :
: is used for, and its importance. After covering statistical and traditiona :
: machine learning methods for anomaly detection using Scikit-Learn in :
: Python, the book then provides an introduction to deep learning with :
: details on how to build and train a deep learning model in both Keras and :
: PyTorch before shifting the focus to applications of the following deep :
: learning models to anomaly detection: various types of Autoencoders, :
: Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional :
: Networks. The book explores unsupervised and semi-supervised anomaly :
: detection along with the basics of time series-based anomaly detection. By :
: the end of the book you will have a thorough understanding of the basic :
: task of anomaly detection as well as an assortment of methods to approach :
: anomaly detection, ranging from traditional methods to deep learning. :
: Additionally, you are introduced to Scikit-Learn and are able to create :
: deep learning models in Keras and PyTorch. What You Will Learn Understand :
: what anomaly detection is and why it is important in today's world Become :
: familiar with statistical and traditional machine learning approaches to :
: anomaly detection using Scikit-Learn Know the basics of deep learning in :
: Python using Keras and PyTorch Be aware of basic data science concepts for :
: measuring a model's performance: understand what AUC is, what precision an :
: recall mean, and more Apply deep learning to semi-supervised and :
: unsupervised anomaly detection Who This Book Is For Data scientists and :
: machine learning engineers interested in learning the basics of deep :
: learning applications in anomaly detection :
. :
.:
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Files
| Path | Size |
|---|
| bb-beginning.anomaly.detection.us.nfo | 10,78 KB |
| bbzcs6ea.zip | 42,10 MB |