Автор: Foster Provost Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking ISBN: 1449361323 ISBN-13(EAN): 9781449361327 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть (1 шт.) Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.
Автор: Guangren Shi Название: Data Mining and Knowledge Discovery for Geoscientists ISBN: 0124104371 ISBN-13(EAN): 9780124104372 Издательство: Elsevier Science Рейтинг: Цена: 15159.00 р. Наличие на складе: Поставка под заказ.
Описание: Addresses challenges by summarizing the developments in geosciences data mining and arming scientists with the ability to apply key concepts to effectively analyze and interpret vast amounts of critical information. This title focuses on 22 of data mining`s practical algorithms and application samples.
Автор: Martin Atzmueller; Alvin Chin; Christoph Scholz; C Название: Mining, Modeling, and Recommending `Things` in Social Media ISBN: 3319147226 ISBN-13(EAN): 9783319147222 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed joint post-workshop proceedings of the 4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013, held in Prague, Czech Republic, in September 2013, and the 4th International Workshop on Modeling Social Media, MSM 2013, held in Paris, France, in May 2013.
Автор: Finger Lutz, Dutta Soumitra Название: Data Mining: Mining Social Media Data to Build a Better Business ISBN: 1449336752 ISBN-13(EAN): 9781449336752 Издательство: Wiley Рейтинг: Цена: 3800.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This non-technical guide shows you how to extract significant business value from big data with Ask-Measure-Learn, a system that helps you ask the right questions, measure the right data, and then learn from the results.
Автор: Xu & Li Название: Social Media Mining And Social Network Analysis ISBN: 1466628065 ISBN-13(EAN): 9781466628069 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 25502.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The widespread use of web-based communities, social media, and social networking sites has brought a rapid change to the interaction between computers and users as well as the digital experience as a whole. <br><br><em>Social Media Mining and Social Network Analysis: Emerging Research</em> highlights the advancements made in social network analysis and social web mining and its influence in the fields of computer science, information systems, sociology, organisation science discipline and much more. This collection of perspectives on developmental practice is useful for industrial practitioners as well as researchers and scholars.
Автор: Bonzanini, Marco Название: Mastering social media mining with python ISBN: 1783552018 ISBN-13(EAN): 9781783552016 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes
Key Features
Leverage the new features of the IPython notebook for interactive web-based big data analysis and visualization
Become an expert in high-performance computing and visualization for data analysis and scientific modeling
A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations
Book Description
IPython is at the heart of the Python scientific stack. With its widely acclaimed web-based notebook, IPython is today an ideal gateway to data analysis and numerical computing in Python.
IPython Interactive Computing and Visualization Cookbook contains many ready-to-use focused recipes for high-performance scientific computing and data analysis. The first part covers programming techniques, including code quality and reproducibility; code optimization; high-performance computing through dynamic compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
What you will learn
Code better by writing high-quality, readable, and well-tested programs; profiling and optimizing your code, and conducting reproducible interactive computing experiments
Master all of the new features of the IPython notebook, including the interactive HTML/JavaScript widgets
Analyze data with Bayesian and frequentist statistics (Pandas, PyMC, and R), and learn from data with machine learning (scikit-learn)
Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
Learn how to write blazingly fast Python programs with NumPy, PyTables, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA and OpenCL), parallel IPython, MPI, and many more
Автор: Lior Rokach Название: Data Mining with Decision Trees ISBN: 981459007X ISBN-13(EAN): 9789814590075 Издательство: World Scientific Publishing Цена: 16632.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.
This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.
This book invites readers to explore the many benefits in data mining that decision trees offer:
Self-explanatory and easy to follow when compacted
Able to handle a variety of input data: nominal, numeric and textual
Scales well to big data
Able to process datasets that may have errors or missing values
High predictive performance for a relatively small computational effort
Available in many open source data mining packages over a variety of platforms
Useful for various tasks, such as classification, regression, clustering and feature selection
Автор: Szabo Gabor, Boykin Oscar Название: Social Media Data Mining and Analytics ISBN: 1118824857 ISBN-13(EAN): 9781118824856 Издательство: Wiley Рейтинг: Цена: 5542.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Written by Dr.
Автор: Brown Meta S. Название: Data Mining for Dummies ISBN: 1118893174 ISBN-13(EAN): 9781118893173 Издательство: Wiley Рейтинг: Цена: 5067.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.
Автор: Ratner Bruce Название: Statistical and Machine-Learning Data Mining ISBN: 1439860912 ISBN-13(EAN): 9781439860915 Издательство: Taylor&Francis Рейтинг: Цена: 9033.00 р. Наличие на складе: Нет в наличии.
Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.
Автор: Jiawei Han Название: Data Mining: Concepts and Techniques, ISBN: 0123814790 ISBN-13(EAN): 9780123814791 Издательство: Elsevier Science Рейтинг: Цена: 9720.00 р. Наличие на складе: Поставка под заказ.
Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.
Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques 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. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>
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