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  • Sách/Book

  • Artificial intelligence.

    • Authors: Zhi-Hua Zhou (2018)

  • This book constitutes the refereed proceedings of the First CCF International Conference on Artificial Intelligence, CCF-ICAI 2018, held in Jinan, China in August, 2018. The 17 papers presented were carefully reviewed and selected from 82 submissions. The papers are organized in topical sections on unsupervised learning, graph-based and semi-supervised learning, neural networks and deep learning, planning and optimization, AI applications.
  • Sách/Book

  • Python for R users : a data science approach

    • Authors: Ajay Ohri (2018)

  • The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations-complete with sample code-of R to Python and Python to R.
  • Sách/Book

  • JavaScript Data Structures and Algorithms

    • Authors: Sammie Bae (2019)

  • This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching.
  • Sách/Book

  • Software engineering: a practitioner’s approach

    • Authors: Roger S. Pressman. (2010)

  • The seventh edition of Software Engineering: A Practitioner's Approach has been designed to consolidate and restructure the content introduced over the past two editions of the book. The chapter structure will return to a more linear presentation of software engineering topics with a direct emphasis on the major activities that are part of a generic software process.
  • Sách/Book

  • Artificial Intelligence : Foundations of Computational Agents

    • Authors: David L. Poole (2018)

  • The new edition also features expanded coverage on machine learning material, as well as on the social and ethical consequences of AI and ML. The book balances theory and experiment, showing how to link them together, and develops the science of AI together with its engineering applications.
  • Sách/Book

  • RapidMiner : Data Mining Use Cases and Business Analytics Applications

    • Authors: Markus Hofmann (2013)

  • Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics.
  • Sách/Book

  • Probability and statistics for data science : math + R + data

    • Authors: Norman Matloff (2019)

  • Probability and Statistics for Data Science: Math + R + Data covers "math stat"-distributions, expected value, estimation etc.-but takes the phrase "Data Science" in the title quite seriously: Real datasets are used extensively. All data analysis is supported by R coding. Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.
  • Sách/Book

  • Community health nursing : promoting and protecting the public's health

    • Authors: Judith A. Allender (2010)

  • The book focuses on public health concerns including health promotion and protection, provides strong nursing application coverage, and addresses timely issues such as disaster nursing, urban clients, and clients with disabilities/chronic illness