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    Browsing by Subject Data Mining

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    • TVS.005483_TT_Jesus Barrasa, Maya Natarajan, Jim Webber - Building Knowledge Graphs_ A Practitioner’s Guide (6th Early Release)-O_Reilly Media, Inc. (.pdf.jpg
    • Sách/Book

    • Building Knowledge Graphs: A Practitioner’s Guide

      • Authors: Barrasa, Jesus (2023)

    • This practical book shows data scientists and data engineers how to build their own knowledge graphs. Authors Jesus Barrasa and Jim Webber from Neo4j illustrate common patterns for building knowledge graphs that solve many of today's pressing knowledge management problems. You'll quickly discover how these graphs become increasingly useful as you add data and augment them with algorithms and machine learning.
    • TVS.005208_TT_Rohit Raja, Kapil Kumar Nagwanshi, Sandeep Kumar, K. Ramya Laxmi - Data Mining and Machine Learning Applications-Wiley-Scrivener (2022).pdf.jpg
    • Sách/Book

    • Data mining and machine learning applications

      • 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.
    • TVS.005295_TT_Andres Fortino - Data Mining and Predictive Analytics for Business Decisions-Mercury Learning and Information (2023).pdf.jpg
    • Sách/Book

    • Data mining and predictive analytics

      • 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