Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Probability: With Applications and R
Probability: With Applications and R

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

...
Bayesian Networks in R: with Applications in Systems Biology (Use R!)
Bayesian Networks in R: with Applications in Systems Biology (Use R!)
While there have been significant advances in capturing data from the entities across complex real-world systems, their associations and relationships are largely unknown. Associations between the entities may reveal interesting system-level properties that may not be apparent otherwise. Often these associations are hypothesized...
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms (Synthesis Lectures on Artificial Intelligence and Machine Learning)

Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and...

Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
Bayesian Artificial Intelligence, Second Edition
Bayesian Artificial Intelligence, Second Edition

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian...

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science...
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)

A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering...

Python for Finance: Analyze Big Financial Data
Python for Finance: Analyze Big Financial Data

The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects...

Building Probabilistic Graphical Models with Python
Building Probabilistic Graphical Models with Python

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications

About This Book

  • Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image...
The Mobile MBA: 112 Skills to Take You Further, Faster
The Mobile MBA: 112 Skills to Take You Further, Faster

An MBA is a curious beast: it can accelerate your career, even if it has limited

practical value in day-to-day management.

Top employers hire top MBAs, but not because MBAs have mastered the mysteries of management. An MBA is a hallmark of personal commitment, effort, and ambition which
...
Probabilistic Modelling in Bioinformatics and Medical Informatics
Probabilistic Modelling in Bioinformatics and Medical Informatics

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these...

Result Page: 12 11 10 9 8 7 6 5 4 3 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy