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This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different;
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Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts;
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to Cornish-Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as;
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to Cornish-Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as;
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applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning;
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these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and;
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Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on;...
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skills needed to develop and implement predictive analytics * Apply the principles and techniques of predictive analytics to effectively;
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Predictive analytics has revolutionized marketing practice. It involves using many techniques from data mining, statistics, modelling;
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techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic;
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of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build;
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on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS;
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knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal;
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topics and valuable software provide everything you need to become proficient in today's most widely used business analytics techniques using the;
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* Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types * Packed with practical advice and;
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A high-level, informal look at the different stages of the predictive analytics cycle Understanding ;...
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-validation, model comparison and selection, and data reduction techniques. Full of rich examples, Building Better Models with JMP Pro is an applied;
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Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analyti;...
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Learn advanced techniques to improve the performance and quality of your predictive models Key Features Use ensemble methods to improve the;
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tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used;
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Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers;
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2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data An;...
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Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a;
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This book provides an overview of predictive methods demonstrated by open source software modeling w;...
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Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Pe;...
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core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book;
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Create and run a human resource analytics project with confidence For any human resource professiona;...
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