Поиск по каталогу |
(строгое соответствие)
|
- Профессиональная
- Научно-популярная
- Художественная
- Публицистика
- Детская
- Искусство
- Хобби, семья, дом
- Спорт
- Путеводители
- Блокноты, тетради, открытки
Knowledge Discovery Using Big Data Analytics. With Practical Approach on Hadoop
В наличии
Местонахождение: Алматы | Состояние экземпляра: новый |
Бумажная
версия
версия
Автор: Ruchi Agarwal,Satvik Vats and Sunny Singh
ISBN: 9783659906244
Год издания: 2016
Формат книги: 60×90/16 (145×215 мм)
Количество страниц: 84
Издательство: LAP LAMBERT Academic Publishing
Цена: 23720 тг
Положить в корзину
Способы доставки в город Алматы * комплектация (срок до отгрузки) не более 2 рабочих дней |
Самовывоз из города Алматы (пункты самовывоза партнёра CDEK) |
Курьерская доставка CDEK из города Москва |
Доставка Почтой России из города Москва |
Аннотация: In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).
Ключевые слова: Hadoop, HDFS, K-means clustering, MapReduce, Big Data Analytics, Frequent Itemsets Mining
Похожие издания
Dharmpal Singh Knowledge Discovery Using Data mining and Soft Computing Methodologies. Research oriented book. 2024 г., 256 стр., мягкий переплет Huge amount of data are collected nowadays from different application domains. It is not feasible to analyze all these data manually. Knowledge Discovery in Databases(KDD) is the nontrivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data.Valid stands for the discovered patterns (information)... | 55722 тг | |
Отрасли знаний: Точные науки -> Информатика и программирование Anirban Mitra Knowledge Discovery using Rough Set and Neighborhood Theory. . 2017 г., 220 стр., мягкий переплет This book based on the thesis which focuses on dealing with the applications of the concepts of Rough set theory and Neighbourhood systems in knowledge representation and knowledge discovery from information systems. Also, it presents some work on privacy problems in social networks. The content of the book is distributed in seven chapters,... | 46517 тг | |
Отрасли знаний: Точные науки -> Информатика и программирование -> Информационные технологии Sujata Dash and Bichitrananda Patra Knowledge Discovery using Machine Learning Algorithms. . 2016 г., 192 стр., мягкий переплет The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and... | 42880 тг |