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    Browsing by Subject Data mining

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    Showing results 1 to 8 of 8
    • TVS.005209_TT_D. Binu and B. R. Rajakumar - Artificial Intelligence in Data Mining_ Theories and Applications-Elsevier_ Academic Press (2021).pdf.jpg
    • Sách/Book

    • Artificial intelligence in data mining : theories and applications

      • Authors: - (2021)

    • Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area.
    • TVS.005287_TT_(Sustainable Computing and Optimization) Sachi Nandan Mohanty, Prasenjit Chatterjee, Bui Thanh Hung - Fuzzy Computing in Data Science_ A.pdf.jpg
    • Sách/Book

    • Fuzzy computing in data science : applications and challenges

      • Authors: - (2024)

    • FUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification.
    • TVS.006010_TT_Jake VanderPlas - Python Data Science Handbook_ Essential Tools for Working with Data-O_Reilly Media (2023).pdf.jpg
    • Sách/Book

    • Python data science handbook : essential tools for working with data

      • Authors: Vanderplas, Jacob T (2023)

    • Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, scikit-learn, and other related tools
    • TVS.005250_TT_John Paul Mueller, Luca Massaron - Python for Data Science For Dummies, 3rd Edition-Wiley-Scrivener (2023).pdf.jpg
    • Sách/Book

    • Python for data science for dummies

      • Authors: Mueller, John Paul (2024)

    • Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner's guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights.
    • TVS.000504_TT_ Adi Polak - Scaling Machine Learning with Spark_ Distributed ML with MLlib, TensorFlow, and PyTorch-O_Reilly Media (2023).pdf.jpg
    • Sách/Book

    • Scaling machine learning with Spark : distributed ML with MLlib, TensorFlow, and PyTorch

      • Authors: Polak, Adi (2023)

    • Learn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing data and ML practitioners to collaborate and understand each other better.