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Human-in-the-Loop Machine Learning

* Supervised machine learning design and query strategies to support Human-in-the-Loop systems * Advanced Adaptive Learning approaches;

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Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent

to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses;

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Human and Machine Learning

needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book;

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Computational Trust Models and Machine Learning

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various;

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Applied Machine Learning for Smart Data Analysis

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements;

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Machine Learning and Information Processing

solutions in the areas of advanced computing and data sciences, covering machine learning, artificial intelligence, human-computer interaction, IoT;

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Thoughtful Machine Learning

Learn how to apply test-driven development (TDD) to machine-learning algorithms - and catch mistakes that could sink your analysis. In this;

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Intelligent Learning Systems

intelligence aims not only to mimic human behavior through learning, and also some sort of abstract thinking, knowledge representation and reasoning;

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Machine Learning and Information Processing

, artificial intelligence, human-computer interaction, IoT, deep learning, image processing and pattern recognition, and signal and speech processing.;

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ICDSMLA 2019

. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human-Computer Interaction;

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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging

, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models;

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Signal Processing and Machine Learning with Applications

presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine;

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Artificial Intelligence and Machine Learning

processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.;

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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions;

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the;

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Statistical Machine Learning for Human Behaviour Analysis

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Machine Learning The New AI

systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product;

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Deep Learning with TensorFlow 2 and Keras

intelligently, using one part of a sequence to correctly interpret another Apply deep learning to natural human language and interpret natural language;

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Challenges in Machine Generation of Analytic Products from Multi-Source Data

, with special attention to learning from small data, using multi-source data, adversarial learning, and understanding the human-machine;

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Hands-On Machine Learning with IBM Watson

Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features Implement data;

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Neural Machine Translation

and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural;

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Transactional Machine Learning with Data Streams and AutoML

frictionless (require minimal to no human intervention) and elastic (machine learning solutions that can scale up or down by controlling the number;

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Machine Learning for Oracle Database Professionals

Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle's;

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Machine Learning with SAP

Work smarter with machine learning! Begin with core machine learning concepts-types of learning, algorithms, data preparation, and more;

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Machine Learning with scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;

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Machine Learning Applications Using Python

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies;

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Machine Learning for Finance

learning and how to put them to work in financial industries Clear explanation and expert discussion of how machine learning works, with an;

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