Building Feature Extraction With Machine Learning
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Building Feature Extraction With Machine Learning
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Author : Bharath.H. Aithal
language : en
Publisher: CRC Press
Release Date : 2022-12-29
Building Feature Extraction With Machine Learning written by Bharath.H. Aithal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-29 with Technology & Engineering categories.
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. Features Provides the basics of feature extraction methods and applications along with the fundamentals of machine learning Discusses in detail the application of machine learning techniques in geospatial building feature extraction Explains the methods for estimating object height from optical satellite remote sensing images using Python Includes case studies that demonstrate the use of machine learning models for building footprint extraction and photogrammetric methods for height assessment Highlights the potential of machine learning and geospatial technology for future project developments This book will be of interest to professionals, researchers, and graduate students in geoscience and earth observation, machine learning and data science, civil engineers, and urban planners.
Feature Engineering For Machine Learning
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Author : Alice Zheng
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-03-23
Feature Engineering For Machine Learning written by Alice Zheng and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Computers categories.
Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques
Remote Sensing Based Building Extraction
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Author : Mohammad Awrangjeb
language : en
Publisher: MDPI
Release Date : 2020-03-27
Remote Sensing Based Building Extraction written by Mohammad Awrangjeb and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-27 with Science categories.
Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D
Fundamentals And Methods Of Machine And Deep Learning
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Author : Pradeep Singh
language : en
Publisher: John Wiley & Sons
Release Date : 2022-02-01
Fundamentals And Methods Of Machine And Deep Learning written by Pradeep Singh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Computers categories.
FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.
Rough Sets Fuzzy Sets Data Mining And Granular Computing
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Author : Yiyu Yao
language : en
Publisher: Springer
Release Date : 2015-11-21
Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Yiyu Yao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-21 with Computers categories.
This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2015, held in Tianjin, China in November 2015 as one of the co-located conference of the 2015 Joint Rough Set Symposium, JRS 2015. The 44 papers were carefully reviewed and selected from 97 submissions. The papers in this volume cover topics such as rough sets: the experts speak; generalized rough sets; rough sets and graphs; rough and fuzzy hybridization; granular computing; data mining and machine learning; three-way decisions; IJCRS 2015 data challenge.
Build A Large Language Model From Scratch
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Author : Sebastian Raschka
language : en
Publisher: Simon and Schuster
Release Date : 2024-10-29
Build A Large Language Model From Scratch written by Sebastian Raschka and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-29 with Computers categories.
From the back cover: Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you'll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you'll really understand it because you built it yourself! About the reader: Readers need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs.
The Art Of Feature Engineering
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Author : Pablo Duboue
language : en
Publisher: Cambridge University Press
Release Date : 2020-06-25
The Art Of Feature Engineering written by Pablo Duboue and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-25 with Computers categories.
A practical guide for data scientists who want to improve the performance of any machine learning solution with feature engineering.
Computation Of Artificial Intelligence And Machine Learning
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Author : Amit Kumar Bairwa
language : en
Publisher: Springer Nature
Release Date : 2024-10-22
Computation Of Artificial Intelligence And Machine Learning written by Amit Kumar Bairwa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.
The two-volume set, CCIS 2184-2185, constitutes the refereed proceedings of the First International Conference on Computation of Artificial Intelligence and Machine Learning, ICCAIML 2024, held in Jaipur, India, in January 18–19, 2024. The 60 papers included in these volumes were carefully reviewed and selected from 645 submissions. These papers focus on various subject areas within the field of Artificial Intelligence and Machine Learning, such as Neural Networks and Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Mining and Big Data Analytics, AI in Healthcare and Biomedical Applications, Autonomous Systems and Robotics, AI Ethics and Fairness, AI in Finance and Eco-nomics.
Recent Advances In Papillary Thyroid Carcinoma Diagnosis And Predictive Factors
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Author : Erivelto Martinho Volpi
language : en
Publisher: Frontiers Media SA
Release Date : 2023-11-09
Recent Advances In Papillary Thyroid Carcinoma Diagnosis And Predictive Factors written by Erivelto Martinho Volpi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-09 with Medical categories.
Intelligent Information And Database Systems
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2022-12-08
Intelligent Information And Database Systems written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-08 with Computers categories.
This book constitutes the refereed proceedings of the 14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022, held Ho Chi Minh City, Vietnam in November 2022. The 113 full papers accepted for publication in these proceedings were carefully reviewed and selected from 406 submissions. The papers of the 2 volume-set are organized in the following topical sections: data mining and machine learning methods, advanced data mining techniques and applications, intelligent and contextual systems, natural language processing, network systems and applications, computational imaging and vision, decision support and control systems, and data modeling and processing for industry 4.0. The accepted and presented papers focus on new trends and challenges facing the intelligent information and database systems community.