- Recording, musical
Authors: Dan Coates (1999) - Responding to popular demand, Dan Coates has compiled a complete collection of 77 great songs for all occasions, to be played by the advanced piano player. Titles include love and wedding favorites, Broadway standards, pop and country ballads, movie and TV hits, and many more. Two selections Colors of the Wind and Star Wars are included on the Royal Conservatory of Music Popular Selection List (2009 Ed.) (These arrangements were originally published in item #AF9842.)
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Authors: Dan LeRoy (2023) - "The never-before told story of drum machines, from their primitive beginnings to their Eighties dominance to the ways they're still changing music today"--
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Authors: - (-) - This programme includes a summary of that process and explores specific areas of data analysis that might be applicable to learners studying at undergraduate and post graduate levels. It aims to provide a definition of qualitative and quantitative data analysis and opportunities to explore photographic, video, textual and numerical data analysis through providing worked examples and further opportunities for learners to develop knowledge and skills in data analysis. The programme also aims to support the development of critical appraisal skills, thorough considering the critical review of research papers. The aims are achieved through captialising on the interactive opportunities of o...
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Authors: Gábor Békés (2023) - This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy.
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Authors: - (-) - Data Analysis, Statistics, and Probability introduces statistics as a problem-solving process. In this course, you will build your skills through investigations of different ways to collect and represent data and to analyze and interpret variation in data. The course consists of 10 sessions, each with a half hour of video programming, problem-solving activities provided online and in a print guide, and interactive activities and demonstrations on the Web.
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Authors: Pushpa Singh (2024) - This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations.
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Authors: Yashawi Karnati (2024) - This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes
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- Book
Authors: William Stallings (2007) - This timely revision of an all-time best-seller in the field features the clarity and scope of a Stallings classic. This comprehensive volume provides the most up-to-date coverage of the essential topics in data communications, networking, Internet technology and protocols, and standards – all in a convenient modular format. Features updated coverage of multimedia, Gigabit and 10 Gbps Ethernet, WiFi/IEEE 802.11 wireless LANs, security, and much more. Ideal for professional reference or self-study. For Product Development personnel, Programmers, Systems Engineers, Network Designers and others involved in the design of data communications and networking products.
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Authors: Duc Haba (2023) - This book is for data scientists and students interested in the AI discipline. Advanced AI or deep learning skills are not required; however, knowledge of Python programming and familiarity with Jupyter Notebooks are essential to understanding the topics covered in this book
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- Book
Authors: Michael Duck (2003) - A broad introductory text written for computer scientists and engineers, focusing on the fundamental aspects of data communications and computer networks. This second edition has been thoroughly revised to cover current networking issues and technologies. Specific updates include those on networks and their management, transmission technologies, security and encryption. This text is appropriate for modular courses in data communications as well as computer science. It is also a useful source for professionals in related disciplines.
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Authors: William W. Cooper (2007) - This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.
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Authors: William W. Cooper (2000) - Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. Emphasis is placed on the use as well as an understanding of DEA and the topics in this book have been selected and treated accordingly. The objective is to introduce students, researchers, and practitioners in business, economics, engineering, and the sciences to Data Envelopment Analysis.
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Authors: Tari, Zahir (2023) - Data Exfiltration Threats and Prevention Techniques provides readers the knowledge needed to prevent and protect from malware attacks, raising awareness of the increasing number of attacks each year. Provided with a detailed description of the recent advances in data exfiltration detection methods and technologies, the authors discuss details of data breach countermeasures and attack scenarios to show how the reader may identify a potential cyber attack in the real world. Aimed at professionals and students alike, this book highlights a range of machine learning methods that can be used to detect potential data theft, identifying research gaps and the potential to make change in the f...
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Authors: Abdelghny Orogat (-) - Data Lake, as defined in the IBM Redbook, is a set of centralized repositories containing vast amounts of raw data (either structured or unstructured), described by metadata, organized into identifi- able datasets, and available on demand.
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Authors: Ian H. Witten (2005) - -
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Authors: Ian H. Witten (2017) - Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations.
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Authors: Ian H. Witten (2011) - Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations.
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Authors: Raja, Rohit (2022) - The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies.
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Authors: Massou, Luc (2024) - Analyzing Websites presents epistemological and methodological contributions from researchers in Information and Communication Sciences exploring websites as sociotechnical, semi-discursive and communicational devices. This study covers website design as well as their integration into the digital strategies of organizations in the public, associative and private sectors.
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Authors: Fortino, Andres (2023) - "Data mining is a recent development in the area of data analysis (within the last 20 years). With many recent advances in data science, we now have many more tools and techniques available for data analysts to extract information from data sets. This book helps data analysts to move up from simple tools such as Excel for descriptive analytics to answer more sophisticated questions using machine learning. Data mining is a sophisticated and organized activity with a well-defined process encoded in the CRISP-DM standard. In this book, we develop an understanding of the tools and techniques to assist the individual data analyst, but not necessarily a data science team
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