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Big Data Analysis Using Machine Learning for Social Scientists and Criminologists, Song Juyoung


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Цена: 13787.00р.
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Автор: Song Juyoung
Название:  Big Data Analysis Using Machine Learning for Social Scientists and Criminologists
ISBN: 9781527533882
Издательство: Cambridge Scholars
Издательство: Cambridge Scholars Publishing
Классификация:


ISBN-10: 1527533883
Обложка/Формат: Hardcover
Страницы: 311
Вес: 0.48 кг.
Дата издания: 01.07.2019
Язык: English
Издание: Unabridged ed
Размер: 20.57 x 14.99 x 2.29 cm
Читательская аудитория: Professional & vocational
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Поставляется из: США
Описание: This book provides a detailed description of the entire study process concerning gathering and analysing big data and making observations to develop a crime-prediction model that utilises its findings.


Reflections on Irish Criminology: Conversations with Criminologists

Автор: Lynch Orla, Ahmed Yasmine, Russell Helen
Название: Reflections on Irish Criminology: Conversations with Criminologists
ISBN: 3030605922 ISBN-13(EAN): 9783030605926
Издательство: Springer
Цена: 7685.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book explores the development of the discipline of Criminology on the island of Ireland, through conversations with leading criminologists.

Criminal Law for Criminologists

Автор: Cross, Noel
Название: Criminal Law for Criminologists
ISBN: 113860691X ISBN-13(EAN): 9781138606913
Издательство: Taylor&Francis
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Цена: 5970.00 р.
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Описание: Criminal Law for Criminologists is an introduction to criminal law that uses theoretical and practical research to bridge the gap between `the law in the books` (criminal law doctrine) and `the law in action` (criminal justice process).

Practical Machine Learning For Data Analysis Using Python

Автор: Subasi, Abdulhamit
Название: Practical Machine Learning For Data Analysis Using Python
ISBN: 0128213795 ISBN-13(EAN): 9780128213797
Издательство: Elsevier Science
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Цена: 16505.00 р.
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Описание:

Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.


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