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Data Science

2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics;

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Predictive Analytics and Data Mining

Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand;

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Predictive Analytics, Data Mining and Big Data

Predictive analytics, data mining and big data are key topics for organizations who want to leverage the ever increasing amounts;

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Business Analytics, Volume II

, data mining, and an introduction to recent applications of predictive analytics-machine learning, neural networks, and artificial intelligence;

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Fundamentals of Predictive Analytics with JMP, Second Edition

on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the;

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Fundamentals of Predictive Analytics with JMP, Second Edition

on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the;

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Data Mining & Predictive Analytics

apply a unified white box approach to data mining methods and models. This approach is designed to walk readers through the operations and;

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Big Data Analytics

This book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad;

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Predictive Analytics for Marketers

Predictive analytics has revolutionized marketing practice. It involves using many techniques from data mining, statistics, modelling;

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Big Data Analytics

This book constitutes the refereed proceedings of the 6th International Conference on Big Data analytics, BDA 2018, held in Warangal, India;

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Data Mining and Predictive Analysis

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime;

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Advanced Data Mining and Applications

This book constitutes the proceedings of the 16th International Conference on Advanced Data Mining and Applications, ADMA 2020, held;

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Trends and Applications in Knowledge Discovery and Data Mining

Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;

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Recent Developments in Data Science and Business Analytics

processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization;

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Adoption of Data Analytics in Higher Education Learning and Teaching

derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative;

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Predictive Data Mining Models

classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining;

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SAP Predictive Analytics The Comprehensive Guide Rheinwerk Publishing

and the Automated Modeler to the Data Manager and Social Network Analysis. Get predictive analysis working for you. Highlights include;

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Predictive HR Analytics, Text Mining & Organizational Network Analysis with Excel

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Descriptive Data Mining

This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human;

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Rapidminer

Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today's world, the need to master data mining, predictive;

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Discovering Knowledge In Data

The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever;

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Data Mining For Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to;

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Advances on Smart and Soft Computing

, data stream management and analytics, deep learning, data mining applications, information retrieval, cloud computing platforms, parallel;

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Practical Predictive Analytics

mining to understand unstructured data * Develop models on your own PC or in Spark/Hadoop environments * Implement predictive analytics;

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Business Analytics, Volume I

decision making approach that uses statistical and quantitative analysis along with data mining, management science, and fact-based data to measure;

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Harnessing the Power of Analytics

This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different;

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