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Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics

models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data. Students of any other discipline of engineering;

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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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Enhanced Bayesian Network Models for Spatial Time Series Prediction

models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data. Students of any other discipline of engineering;

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Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles

Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For;

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Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles

Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For;

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Modeling Techniques in Predictive Analytics

social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem;

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Data Analytics in Biomedical Engineering and Healthcare

in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and;

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Regression Models For Time Series Analysis

concerning state space models. To conclude, they present a Bayesian approach to prediction and interpolation in spatial data adapted to time series;

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Mastering Predictive Analytics with scikit-learn and TensorFlow

analytics. By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis. What you;

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Fundamentals of Machine Learning for Predictive Data Analytics

data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This;

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Data-Driven Computational Neuroscience

of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial;

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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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Healthcare Analytics Made Simple

them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for;

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Big Data Analytics Methods

and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen;

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Dynamic Prediction in Clinical Survival Analysis

in dynamic prediction Part IV explores dynamic prediction models for survival data using genomic data Dynamic Prediction in Clinical Survival;

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Time-aware Conversion Prediction For E-commerce

-commerce. It proposes time-aware conversion prediction models to solve the problem - what products should be recommended for a given period to;

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Estimation and Prediction for Certain Models of Spatial Time Series

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Estimation and Prediction for Certain Models of Spatial Time Series

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Predictive Analytics and Data Mining

and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its;

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Modeling Multilevel Data in Traffic Safety

flexibilities and effectiveness of the Bayesian hierarchical approach in modelling multilevel structure of traffic safety data.;

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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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Hands-On Predictive Analytics with Python

serve a model's predictions as a web application Who this book is forThis book is for data analysts, data scientists, data engineers, and Python;

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Practical Predictive Analytics and Decisioning Systems for Medicine

. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses;

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Statistical Methods for Spatial Data Analysis

generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random;

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Statistical Methods for Spatial Data Analysis

-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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