Tag: Feature

December 9, 2024

Python Feature Engineering Cookbook, 3rd Edition

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Free Download Python Feature Engineering Cookbook: A complete guide to crafting powerful features for your machine learning models, 3rd Edition by Soledad Galli
English | August 30th, 2024 | ISBN: 9781835883587 | 396 pages | True PDF | 18.10 MB
Leverage the power of Python to build real-world feature engineering and machine learning pipelines ready to be deployed to production

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December 9, 2024

Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images

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Free Download Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images
English | 2024 | ISBN: 981978008X | 200 Pages | PDF EPUB (True) | 51 MB
This book deals with hyperspectral image classification using graph neural network methods, focusing on classification model designing, graph information dissemination, and graph construction. In the book, various graph neural network based classifiers have been proposed for hyperspectral image classification to improve the classification accuracy. This book has promoted the application of graph neural network in hyperspectral image classification, providing reference for remote sensing image processing. It will be a useful reference for researchers in remote sensing image processing and image neural network design.

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December 9, 2024

Building Feature Extraction with Machine Learning

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Free Download Building Feature Extraction with Machine Learning by Bharath.H. Aithal, Prakash P.S.
English | October 8, 2024 | ISBN: 1032263830 | 144 pages | PDF | 7.26 Mb
Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and machine learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others.

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September 16, 2024

Building Feature Extraction with Machine Learning Geospatial Applications

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Free Download Building Feature Extraction with Machine Learning: Geospatial Applications by Bharath.H. Aithal, Prakash P.S.
English | December 29, 2022 | ISBN: 1032255331, 1032263830 | True EPUB | 128 pages | 5.6 MB
Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and machine learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others.

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September 15, 2024

Building Machine Learning Systems with a Feature Store (Second Early Release)

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Free Download Building Machine Learning Systems with a Feature Store (Second Early Release)
English | 2024 | ISBN: 9781098165222 | 450 pages | EPUB | 5.26 Mb
Get up to speed on a new unified approach to building machine learning (ML) systems with batch data, real-time data, and large language models (LLMs) based on independent, modular ML pipelines and a shared data layer. With this practical book, data scientists and ML engineers will learn in detail how to develop, maintain, and operate modular ML systems.

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September 9, 2024

Feature Models AI-Driven Design, Analysis and Applications

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Free Download Feature Models: AI-Driven Design, Analysis and Applications by Alexander Felfernig , Andreas Falkner , David Benavides
English | PDF (True) | 2024 | 126 Pages | ISBN : 3031618734 | 5.9 MB
This book provides a basic introduction to feature modelling and analysis as well as to the integration of AI methods with feature modelling. It is intended as an introduction for researchers and practitioners who are new to the field and will also serve as a state-of-the-art reference to this audience. While focusing on the AI perspective, the book covers the topics of feature modelling (including languages and semantics), feature model analysis, and interacting with feature model configurators. These topics are discussed along the AI areas of knowledge representation and reasoning, explainable AI, and machine learning.

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