Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, 2nd Edition

Автор: literator от 14-10-2020, 11:52, Коментариев: 0

Категория: КНИГИ » ОС И БД

Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, 2nd EditionНазвание: Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, 2nd Edition
Автор: Dursun Delen
Издательство: FT Press
Год: 2020
Страниц: 410
Язык: английский
Формат: epub
Размер: 27.8 MB

Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students. Delen’s holistic approach covers all this, and more:

Data mining processes, methods, and techniques
The role and management of data
Predictive analytics tools and metrics
Techniques for text and web mining, and for sentiment analysis
Integration with cutting-edge Big Data approaches

Throughout, Delen promotes understanding by presenting numerous conceptual illustrations, motivational success stories, failed projects that teach important lessons, and simple, hands-on tutorials that set this guide apart from competitors.

Successful business analytics and data science project requires a multitude of software tools and programming languages used collectively and synergistically. Although Python seem to be the most popular analytics tool (programming language), over 90% of the real-world project uses more than one tool. KNIME is a relatively new and rapidly emerging analytics platform. KNIME has several exciting features that differentiates it from the rest. Not only it is free/open-source, visual, easy to learn and use type of tool, but it also has a very active community support, and because of its open architecture, it plays well with other analytics platforms and languages (e.g., Python, R, H2O., Tableau, PowerBI, among others).

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