Computational Statistics Handbook with MATLAB

Author: Wendy L. Martinez
Publisher: CRC Press
ISBN: 1466592745
Category : Business & Economics
Languages : en
Pages : 751

Book Description
A Strong Practical Focus on Applications and AlgorithmsComputational Statistics Handbook with MATLAB, Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the i

Grids, P2P and Services Computing

Author: Frédéric Desprez
Publisher: Springer Science & Business Media
ISBN: 144196794X
Category : Computers
Languages : en
Pages : 207

Book Description
Grids, P2P and Services Computing, the 12th volume of the CoreGRID series, is based on the CoreGrid ERCIM Working Group Workshop on Grids, P2P and Service Computing in Conjunction with EuroPar 2009. The workshop will take place August 24th, 2009 in Delft, The Netherlands. Grids, P2P and Services Computing, an edited volume contributed by well-established researchers worldwide, will focus on solving research challenges for Grid and P2P technologies. Topics of interest include: Service Level Agreement, Data & Knowledge Management, Scheduling, Trust and Security, Network Monitoring and more. Grids are a crucial enabling technology for scientific and industrial development. This book also includes new challenges related to service-oriented infrastructures. Grids, P2P and Services Computing is designed for a professional audience composed of researchers and practitioners within the Grid community industry. This volume is also suitable for advanced-level students in computer science.

Knowledge Exploration in Life Science Informatics

Author: Jesús A. López
Publisher: Springer
ISBN: 3540304789
Category : Computers
Languages : en
Pages : 258

Book Description
This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.

Pattern Classification

Author: Richard O. Duda
Publisher: John Wiley & Sons
ISBN: 111858600X
Category : Technology & Engineering
Languages : en
Pages : 680

Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

A MATLAB Exercise Book

Author: Ludmila Kuncheva
Publisher: Lulu.com
ISBN: 1291784799
Category : Education
Languages : en
Pages : 165

Book Description
A practical guide to problem solving using MATLAB. Designed to complement a taught course introducing MATLAB but ideally suited for any beginner. This book provides a brief tour of some of the tasks that MATLAB is perfectly suited to instead of focusing on any particular topic. Providing instruction, guidance and a large supply of exercises, this book is meant to stimulate problem-solving skills rather than provide an in-depth knowledge of the MATLAB language.

MATLAB For Dummies

Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1119796881
Category : Computers
Languages : en
Pages : 503

Book Description
Go from total MATLAB newbie to plotting graphs and solving equations in a flash! MATLAB is one of the most powerful and commonly used tools in the STEM field. But did you know it doesn’t take an advanced degree or a ton of computer experience to learn it? MATLAB For Dummies is the roadmap you’ve been looking for to simplify and explain this feature-filled tool. This handy reference walks you through every step of the way as you learn the MATLAB language and environment inside-and-out. Starting with straightforward basics before moving on to more advanced material like Live Functions and Live Scripts, this easy-to-read guide shows you how to make your way around MATLAB with screenshots and newly updated procedures. It includes: A comprehensive introduction to installing MATLAB, using its interface, and creating and saving your first file Fully updated to include the 2020 and 2021 updates to MATLAB, with all-new screenshots and up-to-date procedures Enhanced debugging procedures and use of the Symbolic Math Toolbox Brand new instruction on working with Live Scripts and Live Functions, designing classes, creating apps, and building projects Intuitive walkthroughs for MATLAB’s advanced features, including importing and exporting data and publishing your work Perfect for STEM students and new professionals ready to master one of the most powerful tools in the fields of engineering, mathematics, and computing, MATLAB For Dummies is the simplest way to go from complete newbie to power user faster than you would have thought possible.

Exploratory Data Analysis with MATLAB

Author: Wendy L. Martinez
Publisher: CRC Press
ISBN: 1315349841
Category : Mathematics
Languages : en
Pages : 589

Book Description
Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data

Pattern Recognition and Machine Learning

Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Category : Computers
Languages : en
Pages : 0

Book Description
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Machine Learning

Author: Stephen Marsland
Publisher: CRC Press
ISBN: 1420067192
Category : Business & Economics
Languages : en
Pages : 407

Book Description
Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but

Interpretable Machine Learning

Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320

Book Description
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.