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Effective Statistical Learning Methods for Actuaries II

Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data;

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Effective Statistical Learning Methods for Actuaries I

Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data;

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Probability and Statistics for Actuaries

Probability and Statistics for Actuaries provides students with a structured and detailed explanation of the probabilistic and statistical;

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Modelling Mortality with Actuarial Applications

rate, Part I shows how and why to build statistical models, based on data at the level of the individual persons in a pension scheme or life;

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Tree-Based Methods for Statistical Learning in R

This book provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I;

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Predictive Modeling Applications In Actu

is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples;

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Introduction to Actuarial and Financial Mathematical Methods

This self-contained module for independent study covers the subjects most often needed by non-mathematics graduates, such as;

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Statistical Methods with Applications to Demography and Life Insurance

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes;

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Statistical Methods with Applications to Demography and Life Insurance

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes;

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Statistics and Machine Learning Methods for EHR Data

The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning;

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Introduction to Statistical and Machine Learning Methods for Data Science

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Introduction to Statistical and Machine Learning Methods for Data Science

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Statistical Thinking: Improving Business Performance

the computer is used for computational details, the authors describe the role of statistical thinking and methods for problem solving and;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Statistical Mechanics and Thermodynamics

A textbook on statistical mechanics and thermodynamics, suitable for a graduate-level physics course. Covers Boltzmann systems, quantum;

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Financial Mathematics For Actuaries

Financial Mathematics For Actuaries;

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An Introduction to Statistical Learning

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for;

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An Introduction to Statistical Learning

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for;

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Advance Statistical Method For Water Analysis

I am very happy to publish this book for advance method for water study. This book contains the advance methods for water testing;

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Choosing a Quality Control System

and buzzwords suggested for implementing these systems and to assist in learning about these systems and techniques; there are well over 200;

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Choosing a Quality Control System

and buzzwords suggested for implementing these systems and to assist in learning about these systems and techniques; there are well over 200;

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Supervised Machine Learning

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises;

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Trading Systems and Methods

turned to Trading Systems and Methods for detailed information on indicators, programs, algorithms, and systems, and now this fully;

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Machine Learning and Knowledge Discovery in Databases

track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier;

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Boosted Statistical Relational Learners

combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational;

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Machine Learning and Knowledge Discovery in Databases

. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection;

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Machine Learning and Knowledge Discovery in Databases

. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection;

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