Showing results for "anna ciampi"
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Data Mining Techniques in Sensor Networks
Summarization, Interpolation and Surveillance
2013
EN
Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is...
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Data Analysis with Open Source Tools
A Hands-On Guide for Programmers and Data Scientists
2010
EN
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through...
1998
EN
Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial...
1997
EN
Confusing Textbooks? Missed Lectures? Not Enough Time?Fortunately for you, there's Schaum's Outlines. More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test y...
2007
EN
This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one of the R Core Development Team, and by an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the ground-breaking R system, this book emphasizes programming, including the principles that apply to most comp...
Applied Geostatistics with SGeMS
A User's Guide
2009
EN
The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the use...
2015
EN
Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role. The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation. GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises.
2013
EN
A thoroughly revised new edition of the definitive work on power systems best practicesIn this eagerly awaited new edition, Power Generation, Operation, and Control continues to provide engineers and academics with a complete picture of the techniques used in modern power system operation. Long recognized as the standard reference in the field, the book has been thoroughly updated to reflect the enormous changes that have taken place in the electric power industry ...
Financial Modelling
Theory, Implementation and Practice with MATLAB Source
2012
EN
Financial modellingTheory, Implementation and Practice with MATLAB SourceJörg Kienitz and Daniel WetterauFinancial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocatio...
Essentials of Monte Carlo Simulation
Statistical Methods for Building Simulation Models
2012
EN
Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each out...
Modeling and Dimensioning of Mobile Wireless Networks
From GSM to LTE
2010
EN
This book is a must-read for all network planners and other professionals wishing to improve the quality and cost efficiency of 3G and LTE networksIn this book, the authors address the architecture of the 2/3G network and the Long Term Evolution (LTE) network. The book proposes analytical models that make the analysis and dimensioning of the most important interfaces, i.e. WCDMA or Iub, possible. Furthermore, the authors include descriptions of fundamental technolo...
- Series -
- Engineering (R0)
2016
EN
This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for cer...











