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Carlos Alberto Reyes Garcia: Exploring
Infant Cry

Exploring Infant Cry

Medical and Technical Analysis and Signal Processing Perspectives

Intelligence-Based Medicine: Subspecialty Series

Artificial Intelligence Based Primary Care: Artificial Intelligence and Human Cognition in General Practice and Family Medicine provides a comprehensive look into the integration of artificial intelligence within primary care. This book aims to bridge the gap between data scientists and primary care clinicians by presenting potential AI applications, implementation challenges, and real-world clinical scenarios in an accessible manner. Comprised of 5 sections and 20 chapters, it offers both theoretical insights and practical guidance for family medicine practitioners. Additionally, the book includes a chapter dedicated to a day in the life of a General Practitioner, showcasing the practical impact of AI. It also features an extra compendium listing the Top 100 articles and best books on Artificial Intelligence. This resource is invaluable for academics, researchers, and clinicians eager to expand their knowledge in this emerging field.

Artificial Intelligence and Human Cognition in General Practice and Family Medicine

Artificial Intelligence Based Primary Care

Shortest Histories

The Shortest History of AI

Integration of Federated Learning and Blockchain for Smart Cities

Quantum Computing and Machine Learning for 6G

Advances in Biomedical Applications

Nanotheranostics

Plant-Derived Anti-Cancer Drugs

Sybex Study Guide

A fast and efficient prep handbook for the Azure AI Fundamentals certification exam In MC Microsoft Certified Azure AI Fundamentals Study Guide: Exam AI-900, experienced software engineer Adora Nwodo walks you through every technical topic you need to understand to succeed on the AI-900 certification exam and build a fundamental understanding of Azure AI features. The Study Guide uses the proven and popular Sybex approach to help you use Azure AI in the real-world, whether you're in a technical or non-technical role. Nwodo offers clear explanations, step-by-step instructions, and visual aids to guide you through essential AI concepts and shows you how to use them in the Azure cloud. You'll learn about: <ul> <li>Artificial intelligence concepts and workloads</li> <li>Responsible AI use in Azure</li> <li>Core concepts in AI models and solutions</li> <li>Introduction to machine learning concepts, including data preprocessing, training and validation, algorithms, and more</li> <li>The application of machine learning concepts on the Azure cloud platform</li> <li>Computer vision in Azure</li> <li>Natural language processing concepts</li> <li>Generative AI concepts</li> <li>The Azure OpenAI Service</li> <li>Example AI use cases and industry-specific applications</li> </ul> The MC Microsoft Certified Azure AI Fundamentals Study Guide highlights best practices for industry newcomers and veterans alike and builds the confidence you need to pass the AI-900 certification exam on your first attempt. Inside the book: <ul> <li>Intuitively organized material and additional sample questions that allow you to selectively study the areas in which you need to improve</li> <li>Carefully explained content appropriate for non-technical professionals who interact with AI technologies occasionally or on a daily basis</li> <li>Complimentary access to the superior Sybex online learning environment and test bank, including practice test questions, digital flashcards, and a glossary of key terms</li> </ul> Perfect for everyone preparing for the AI-900 certification exam, the Microsoft Certified Azure AI Fundamentals Study Guide is also a must-read for technical and non-technical professionals--especially those working in AI-impacted industries like sales and marketing--who wish to expand their AI skillset and improve their effectiveness at work.

Exam AI-900

MC Azure AI Fundamentals Study Guide

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains. It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Advanced Intelligence Methods for Data Science and Optimization

A Systems Thinking Approach

Engineering Principles, Methods, and Applicationsin the Age of AI

An Introduction to String Algorithms

Techniques and Applications

Deep Learning for Intrusion Detection

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

Exploring Infant Cry

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