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Gesamtkatalog

Catalogue complet

Shiyan Xu: Apache Hudi - The Definitive
Guide

Apache Hudi - The Definitive Guide

Building Robust, Open, and High-Performing Data Lakehouses

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

AK Peters Visualization Series

The book explores real-world datasets, uncovering hidden patterns and gaining insights along the way. The book is filled with illustrations using practical examples, Python codes, and different types of exercises designed to reinforce the concepts and processes discussed.

Descriptive Analysis, Visualization, and Dashboard Design (with codes in Python)

Exploratory Data Analysis

Data-Directed Mathematical Modeling

This comprehensive compendium explains the technical challenges and opportunities behind the most recent and successful applications in artificial intelligence [AI] and data analytics. It focuses on applications that have the power to be adapted to many different fields and explains how AI can be implemented as an assistant in digital humanities. It also introduces new methods and applications in classification trees, networks, and Bayesian learning.The useful reference text benefits professionals, academics, researchers, and graduate students in AI/machine learning, neural networks, and bioinformatics, and digital humanities.

Probing The Past With Data Analytics And Ai

A Statistical Guide to Certainty in an Uncertain World

What Are the Odds?

In an effort to investigate the revolutionary potential of AR and VR technologies in the field of mechanical and medical emergency management, "Virtual Realities, Real Emergencies" was written. This book seeks to educate readers on how augmented and virtual reality (AR/VR) may transform response to emergencies, boost training, and facilitate better decision-making under pressure. It aims to equip professionals and hobbyists alike to use these immersive technologies for saving lives and minimizing calamities by analyzing real-world applications, cutting-edge breakthroughs, and practical insights. The ground-breaking book "Virtual Realities, Real Emergencies: Integrating AR/VR in Mechanical and Medical Crisis Management" has two goals: to teach and to give readers agency in times of crisis. Our goal is to educate both industry experts and casual observers on the revolutionary possibilities of AR and VR in the high-stakes arenas of mechanical and medical emergency response. The gap between theory and practice is something we want to close by providing real-world insights, practical counsel, and examples of achievement. Our goal is to educate the public on the potential life-saving benefits of AR and VR technology, demystify these tools for the general reader, and provide concrete measures for incorporating them into existing emergency response procedures. This book not only celebrates the technological advances that have been accomplished but also calls for more cooperation to ensure that these innovations are implemented in a way that puts people's lives first during emergencies.

Integrating AR/VR in Computing and Medical Crisis Management

Virtual Reality, Real Emergency

Written by a data scientist with decades of practical experience on some of the most challenging datasets, this book caters to both novices and professionals working in the fields of data science and machine learning. It enables novices to enter these fields with confidence and ease. There are no formal prerequisites. An introduction to Python is included. The book then proceeds to cover some of the language's most advanced features. The mathematical foundations that follow are meticulously explained. The discussion then proceeds to a practical consideration of data science and machine learning. The material is delivered through case studies developed on real datasets. The reader is invited to follow these case studies, and so develop experience in working with real data. Numerous solved exercises make this work suitable for self-study. The contents of this book have been taught by the author to students of different age groups and levels of experience at Imperial College London and at the Thalesians Intensive Summer School in Artificial Intelligence over the years.

Introduction To Python For Quantitative Finance, An: From Scratch To Productivity

Apache Hudi - The Definitive Guide

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