Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Bibliography : page 681-734. Index : page 735-752.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, 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. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know abo…
Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. Included Appendix, Bibliography, and Index
Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner's guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as…
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern s…
Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guideAbout This Book* Manipulate your data by exploring, transforming, validating, and integrating it using Pentaho Data Integration 8 CE* A comprehensive guide exploring the features of Pentaho Data Integration 8 CE* Connect to any database engine, explore the databases, and perform all kind of operatio…
This book tells a practical guide to using Python for data science and analysis. Index : page 551-563.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers f…
Previous editions titled: Computer-assisted reporting.
With coverage of the entire research process in social media, data collection and analysis on specific platforms, and innovative developments in the field, this handbook is the ultimate resource for those looking to tackle the challenges that come with doing research in this sphere
In this book, you'll find 54 hands-on descriptions that help you do the key methods used in service design. These methods include instructions, guidelines, and tips-and-tricks for activities within research, ideation, prototyping, and facilitation. This is the print version of the method companion to the book This Is Service Design Doing (#TiSDD). It includes the same content that you can find …
The definitive guide to using data and technology in reporting, this text teaches students how to combine data analysis with traditional reporting to create compelling stories. Through coverage of theory, practical examples, online tutorials, and celebrated stories from around the world, thistext demonstrates the tools and principles of data-driven journalism.
Derive useful insights from your data using Python. Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem. Text Analytics with Python teaches you both basic and advanced concepts, including text and language syntax, structure, semantics. You will focus on algorithms and techniques,…
Tackle a variety of tasks in natural language processing by learning how to use the R language and tidy data principles. This practical guide provides examples and resources to help you get up to speed with dplyr, broom, ggplot2, and other tidy tools from the R ecosystem. You’ll discover how tidy data principles can make text mining easier, more effective, and consistent by employing tools al…
This book gives a comprehensive coverage of state-of-the-art big data analytics in cybersecurity and IT management. The topics include threat analysis, vulnerability identification, mission analysis, network monitoring, network management, visualization, and cybertraining. Each topic is examined in detail in a case study.
A practical, skill-based introduction to data analysis and literacy We are swimming in a world of data, and this handy guide will keep you afloat while you learn to make sense of it all. In Data Literacy: A User's Guide, David Herzog, a journalist with a decade of experience using data analysis to transform information into captivating storytelling, introduces students and professionals to the …
"Designing, developing, and delivering data visualizations"--Cover.
"A project of the European Journalism Centre and the Open Knowledge Foundation."--T.p. verso.