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statistical problems using Python; * Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems;
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Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features A step-by-step guide to conduct Bayesian;
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methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various;
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This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical;
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computers perform Bayesian inference * Using the PyMC Python library to program Bayesian analyses * Building and debugging models with PyMC;
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Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common;
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and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis;
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Learn how to apply powerful data analysis techniques with popular open source Python modules About This Book * Find, manipulate, and;
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and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods;
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Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the;
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Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the;
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This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to;
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Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book * Clean, format;
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as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes;
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This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will;
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Bayesian Approaches in Oncology Using R and OpenBUGS serves two audiences: those who are familiar with the theory and applications;
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This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale;
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Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting;
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geospatial analysis workflows using Python Code the simplest possible GIS in just 60 lines of Python Create thematic maps with Python tools such as;
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analysis with Python, then this book is for you. Familarity with digital mapping and analysis using Python or another scripting language for;
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comfortable in performing data exploration and analysis on Python using pandas Step-by-step demonstration of using Python and pandas with interactive;
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operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data;
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This book gets you up and running with doing complex Bayesian statistics, focussing on applied analysis rather than maths.;
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This book gets you up and running with doing complex Bayesian statistics, focussing on applied analysis rather than maths.;
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introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work;
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, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR;
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estimate of the unknown. Beyond presenting Bayesian theory and methods of analysis, the text is illustrated with a variety of applications to real;
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