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Ensemble Learning

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends;

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Ensemble Classification Methods with Applications in R

An essential guide to two burgeoning topics in machine learning - classification trees and ensemble learning Ensemble Classification;

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Machine Learning

introduction to the core concepts, approaches, and applications of machine learning. The author-an expert in the field-presents fundamental ideas;

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Statistical Reinforcement Learning

is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the;

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Statistical Reinforcement Learning

is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the;

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Modern Approach to Educational Technologies

of approaches in education and related technologies. It includes introduction to instructional technology, instructional design and its models;

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Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research

of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon;

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Ensemble Machine Learning Cookbook

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular;

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An Introduction to Quantum Transport in Semiconductors

Green's functions starting from equilibrium Green's functions and going through modern time-dependent approaches to non-equilibrium Green's;

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An Introduction to Approaches and Modern Applications with Ensemble Learning

attention in recent years in the ML and AI. Each chapter opens with an introduction to ML and EL techniques, and then, analyzes the applications;

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Temporal Data Mining via Unsupervised Ensemble Learning

ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich;

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Entropy Guided Transformation Learning

experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with;

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Ensemble Learning for AI Developers

the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn how to change;

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Ensembles in Machine Learning Applications

(SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery;

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Artificial Intelligence Basics

intelligence machines and robotics is comprehensive with numerous modern applications. Features: Covers an introduction to concepts related to AI;

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Hands-On Ensemble Learning with R

machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world;

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Methods for Neural Ensemble Recordings

recordings, contributions define global brain states and propose conceptual and technical approaches to human neural ensemble recordings in the;

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Biometric Security and Privacy: Opportunities & Challenges in the Big Data Era

approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics;

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Biometric Security and Privacy: Opportunities & Challenges in the Big Data Era

approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics;

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Active Learning

frameworks. We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses;

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An Introduction to Machine Learning

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches;

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Ensemble Methods

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms;

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Concepts and Real-Time Applications of Deep Learning

in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield;

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Modern Experimental Design

A complete and well-balanced introduction to modern experimental design Using current research and discussion of the topic along with;

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Introduction To Econometrics Update

students grasp the relevance of econometrics with Introduction to Econometrics-the text that connects modern theory and practice with motivating;

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Introduction To Econometrics

students grasp the relevance of econometrics with Introduction to Econometrics--the text that connects modern theory and practice with engaging;

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Theories of Counseling and Psychotherapy

collaboration. Practical yet rigorous, the text is a state-of-the-art introduction to contemporary approaches in counseling and psychotherapy for;

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