Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. Beginning with straightforward option pricing on binomial trees, the book...

• A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
• Get to grips with the basics of Predictive...

This vintage guide from over a century ago offers timeless, practical advice on building log cabins. Plans and directions for simple structures are easy enough for amateurs to follow; time and inclination are the only necessary elements. Each of the designs has been tested and allows numberless alterations to suit the builder's tastes and...

Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms...

Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are...

In this textbook, I take an unconventional approach to data analysis. Its contents are heavily influenced by the idea that data analysis should help in enhancing and augmenting knowledge of the domain as represented by the concepts and statements of relation between them. According to this view, two main pathways for data analysis are...

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully...