-
Author Antonios Chorianopoulos , Konstantinos K. Tsiptsis
This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segm....
Release Date 2010/03 -
Author Christopher J. Pal , Mark A. Hall , Eibe Frank , Ian H. Witten
Data Mining: Practical Machine Learning Tools and Techniques, Fourth 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. This highly anticipated ....
Release Date 2016/10 -
Data Model Scorecard: Applying the Industry Standard on Data Model Quality
Author Steve Hoberman
Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it's essential to get the data model right. But how do you determine ....
Release Date 2015/10 -
Author Steve Hoberman
Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio's support for agile development, as w....
Release Date 2015/11 -
Author Kirk Munroe
Save time analyzing volumes of data using best practices to extract, model, and create insights from your dataKey FeaturesMaster best practices in data modeling with Tableau Prep Builder and Tableau DesktopApply Tableau Server and Cloud to create and extend data modelsBuild organizational data model....
Release Date 2022/12 -
Data Preparation for Analytics Using SAS
Author Gerhard Svolba
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data str....
Release Date 2015/04 -
Data Preparation in the Big Data Era
Author Federico Castanedo
Preparing and cleaning data is notoriously expensive, prone to error, and time consuming: the process accounts for roughly 80% of the total time spent on analysis. As this O’Reilly report points out, enterprises have already invested billions of dollars in big data....
Release Date 2015/10 -
Data Preprocessing with Python for Absolute Beginners
This book is dedicated to data preparation and explains how to perform different data preparation techniques on various datasets using different data preparation libraries written in the Python programming language.Key FeaturesA crash course in Python to fill any gaps in prerequisite knowledge and a.... -
Author Malathi Mahadevan
Enjoy reading interviews with more than two dozen data professionals to see a picture of what it’s like to work in the industry managing and analyzing data, helping you to know what it takes to move from your current expertise into one of the fastest growing areas ....
Release Date 2018/10 -
Data Science Algorithms in a Week
Author Dávid Natingga
Build strong foundation of machine learning algorithms In 7 days.About This BookGet to know seven algorithms for your data science needs in this concise, insightful guideEnsure you're confident in the basics by learning when and where to use various data science a....
Release Date 2017/08 -
Data Science and Analytics for SMEs: Consulting, Tools, Practical Use Cases
Author Afolabi Ibukun Tolulope
Master the tricks and techniques of business analytics consulting, specifically applicable to small-to-medium businesses (SMEs). Written to help you hone your business analytics skills, this book applies data science techniques to help solve problems and improve upon many aspects of a business' ope....
Release Date 2022/09 -
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
Author EMC Education Services
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are app....
Release Date 2015/01 -
Data Science and Engineering at Enterprise Scale
Author Jerome Nilmeier
As enterprise-scale data science sharpens its focus on data-driven decision making and machine learning, new tools have emerged to help facilitate these processes. This practical ebook shows data scientists and enterprise developers how the notebook interface, Apac....
Release Date 2019/04 -
Data Science at the Command Line, 2nd Edition
Author Jeroen Janssens
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data.....
Release Date 2021/09 -
Author Leonard Apeltsin
Data Science Bookcamp doesn’t stop with surface-level theory and toy examples. As you work through each project, you’ll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don’t quite fit the model you’re building. You’ll appreciate the detailed setup instruc....
Release Date 2021/11 -
Data Science Crash Course for Beginners
This course lays the groundwork for further study into data science with Python for those students with little to no experienceKey FeaturesCrash course in Python programming to build or refresh any gaps in prerequisite knowledgeReal-world projects for hands-on practice in various data science tasksA.... -
Data Science Essentials in Python
Author Dmitry Zinoviev
Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and ....
Release Date 2016/08 -
Data Science for Business and Decision Making
Author Patrícia Belfiore , Luiz Paulo Fávero
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quanti....
Release Date 2019/04 -
Data Science For Dummies, 2nd Edition
Author Jake Porway , Lillian Pierson
Your ticket to breaking into the field of data science!Jobs in data science are projected to outpace the number of people with data science skills—making those with the knowledge to fill a data science position a hot commodity in the coming years. Data Science For ....
Release Date 2017/03 -
Data Science for Marketing Analytics
Author Pranshu Bhatnagar , Debasish Behera , Tommy Blanchard
Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise resultsKey FeaturesStudy new techniques for marketing analytics Explore uses of machine learning to power your marketing analyses Work through each stage of d....
Release Date 2019/03 -
Data Science for Modern Manufacturing
Author Li Ping Chu
The world’s leading nations are standing at the precipice of the next great manufacturing revolution—one in which the Industrial Internet of Things (IIoT) and big data analytics are already making a major impact. In this O’Reilly report, author Li Ping Chu shares i....
Release Date 2016/07 -
Data Science from Scratch, 2nd Edition
Author Joel Grus
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows....
Release Date 2019/05 -
Data Science Fundamentals for Python and MongoDB
Author David Paper
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning exper....
Release Date 2018/05 -
Author Deborah Nolan , Duncan Temple Lang
Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered i....
Release Date 2015/09 -
Data Science in Transportation
Author Mike Barlow
Hold on, because we’re entering the age of smart transportation at astonishing speed. By 2020, roughly one in every five vehicles (250 million) will be on the road. Within the next 10 years, the very idea of manually operating a car, truck, ship, plane, or train ma....
Release Date 2017/04 -
Author Chris Fregly , Antje Barth
If you use data to make critical business decisions, this book is for you. Whether you’re a data analyst, research scientist, data engineer, ML engineer, data scientist, application developer, or systems developer, this guide helps you broaden your understanding of the mo....
Release Date 2021/07 -
Data Science Programming All-in-One For Dummies
Author John Paul Mueller , Luca Massaron
Your logical, linear guide to the fundamentals of data science programmingData science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It ....
Release Date 2020/01 -
Author Mohamed Noordeen Alaudeen , Aaron England , Rohan Chopra
Leverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and predict the occurrence of a particular future event.Key FeaturesExplore the depths of data science, from data collection thro....
Release Date 2019/07 -
Data Science with Python and Dask
Author Jesse Daniel
Data Science with Python and Dask teaches you to build scalable projects that can handle massive datasets. After meeting the Dask framework, you’ll analyze data in the NYC Parking Ticket database and use DataFrames to streamline your process. Then, you’ll create ma....
Release Date 2019/07