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pro vyhledávání: '"94(9)"'
Autor:
Karthik Ramasubramanian, Jojo Moolayil
Learn the ropes of supervised machine learning with R by studying popular real-world use-cases, and understand how it drives object detection in driver less cars, customer churn, and loan default prediction.Key FeaturesStudy supervised learning algor
Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians is designed for the application of practical concepts in machine learning to clinical radiation oncology. It addresses the existing void in a resource to educa
Autor:
Olalekan Samuel Ogunleye
We live in an era defined by an avalanche of data, and the challenge lies not merely in its accumulation, but in gleaning meaningful insights from this digital deluge. This monumental task is particularly significant in the realm of government servic
Autor:
Tsutomu Sasao
This book introduces a novel perspective on machine learning, offering distinct advantages over neural network-based techniques. This approach boasts a reduced hardware requirement, lower power consumption, and enhanced interpretability. The applicat
Autor:
KC Santosh, Suprim Nakarmi
Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how b
Autor:
Rituparna Sen, Sourish Das
This book prepares students to execute the quantitative and computational needs of the finance industry. The quantitative methods are explained in detail with examples from real financial problems like option pricing, risk management, portfolio selec
Autor:
Avi Arampatzis, Evangelos Kanoulas, Theodora Tsikrika, Stefanos Vrochidis, Anastasia Giachanou, Dan Li, Mohammad Aliannejadi, Michalis Vlachos, Guglielmo Faggioli, Nicola Ferro
This volume LNCS 14163 constitutes the refereed proceedings of 14th International Conference of the CLEF Association, CLEF 2023, in Thessaloniki, Greece, during September 18–21, 2023. The 10 full papers and one short paper included in this book wer
Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approa
This book is a comprehensive guide to the latest developments in data-driven additive manufacturing (AM). From data mining and pre-processing to signal processing, computer vision, and more, the book covers all the essential techniques for preparing
This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas. This book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frame