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Customer And Business Analytics

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;

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Customer and Business Analytics

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;

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Advanced Data Analytics for Power Systems

industry with backgrounds in power systems engineering, applied mathematics, and computer science.;

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The The Applied SQL Data Analytics Workshop

getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of The Applied SQL Data;

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Applied Advanced Analytics

consists of selected presentations at the 6th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. The;

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Primer for Data Analytics and Graduate Study in Statistics

distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate;

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Primer for Data Analytics and Graduate Study in Statistics

distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate;

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Advanced Analytics with Transact-SQL

Intermediate-Advanced user level;

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Advanced Analytics in Power BI with R and Python

Intermedate-Advanced user level;

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Educational Improvement Through Data Mining & Analytics

data mining) are starting to be applied in education. The book examines the challenges being encountered and the potential of such efforts for;

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Applied Analytics - Quantitative Research Methods

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Advanced Analytics with R and Tableau

Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R About This Book * A;

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Win With Advanced Business Analytics

analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics;

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AI and Machine Learning Paradigms for Health Monitoring System

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed;

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Advanced Analytics and Artificial Intelligence Applications

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Harnessing the Power of Analytics

data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline;

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Applied Health Analytics and Informatics Using SAS

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Advances in Non Destructive Evaluation

encompass a vast spectrum from Conventional to Advanced NDE including novel methods, instrumentation, sensors, procedures and data analytics as;

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Advanced Fixed Income Analytics

Advanced Fixed Income Analytics helps fixed income professionals stay abreast of the latest developments in the field by providing a;

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Human Capital Analytics

An insightful look at the implementation of advanced analytics on human capital Human capital analytics, also known as human resources;

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Big Data Analytics Methods

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers;

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SAP S/4HANA Embedded Analytics

Intermediate-Advanced user level;

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Profit Driven Business Analytics

Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on;

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Applied Analytics through Case Studies Using SAS and R

. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced;

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Getting Started with Salesforce Einstein Analytics

advanced analytics, right in Salesforce. You will manage datasets, query data with Salesforce Analytics Query Language (SAQL), and customize;

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Advanced Data Analytics Using Python

Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark;

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Advanced Data Analytics Using Python

Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark;

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