Practical Machine Learning for Streaming Data with Python : Design, Develop, and Validate Online Learning Models / Sayan Putatunda
A quick start guide for data scientists and machine learning engineers looking to implement machine learning models for streaming ...
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Principles of Mathematics in Operations Research
Principles of Mathematics in Operations Research is a comprehensive survey of the mathematical concepts and principles of ...
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Probability and Risk Analysis
This book presents notions and ideas from the foundations of a statistical treatment of risks. Bayesian methods are frequently ...
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Probability and Risk Analysis
This book presents notions and ideas from the foundations of a statistical treatment of risks. Bayesian methods are frequently ...
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Probability in Electrical Engineering and Computer Science An Application-Driven Course
This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering ...
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Process Optimization
PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial ...
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Proportional Hazards Regression
The place in survival analysis now occupied by proportional hazards models and their generalizations is so large that it ...
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Quantitative Corporate Finance
Guerard and Schwartz cover a wide variety of tools and techniques used to evaluate and manage financial performance, with ...
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Recent Advances in Linear Models and Related Areas : Essays in Honour of Helge Toutenburg
The theory of linear models and regression analysis plays an essential role in the development of methods for the statistical ...
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Regression Methods in Biostatistics
This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used ...
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Researching Elites and Power Theory, Methods, Analyses
This book describes how elite studies theoretically and methodologically construct their object, i.e. how particular conceptualizations ...
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Régression : Théorie et applications = Regression : Theory and Applications
This book explains in detail, with supporting examples, one of the most common statistical methods: regression. The first ...
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Semiparametric Modeling of Implied Volatility
This book fills a gap in the financial literature by bringing together both recent advances in the theory of implied volatility ...
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Statistical Demography and Forecasting
For statisticians the book provides a unique introduction to demographic problems in a familiar language. For demographers, ...
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Statistical Learning from a Regression Perspective
Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the ...
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Statistical Methods for Biostatistics and Related Fields
Biostatistics is one of the scientific fields for which the recent developments have been extremely important. It is also ...
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Statistical Models and Methods for Biomedical and Technical Systems
An outgrowth of the "International Conference on Statistical Models for Biomedical and Technical Systems," this book is ...
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Statistical Models and Methods for Financial Markets
This book presents statistical methods and models of importance to quantitative finance and links finance theory to market ...
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Statistical Reasoning in Medicine
The successful Statistical Reasoning in Medicine: The Intuitive P-value Primer, with its novel emphasis on patient and community ...
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Statistics Applied to Clinical Trials
This book explains classical statistical analyses of clinical trials,andaddresses relatively novel issues, including equivalence ...
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