This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...
This is the first book where mathematics and computer science are directly confronted and joined to tackle intricate problems in computer science with deep mathematical approaches. It contains a collection of refereed papers presented at the Colloquium on Mathematics and Computer Science held at the University of Versailles-St-Quentin on...
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...
Graphics in this book are printed in black and white.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....
Robert Sedgewick has thoroughly rewritten and substantially expanded his popular work to provide current and comprehensive coverage of important algorithms and data structures. Many new algorithms are presented, and the explanations of each...
A friendly and accessible introduction to the most useful algorithms
Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical...
Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more...
A fresh approach and simple way to transform your yard!
The prospect of revamping a yard is daunting. Where do you start? How do all the various areas come together in a beautiful, cohesive way? The Beginner’s Guide to Starting a Garden simplifies the process by showing you how to spend fewer...
Using SAS Enterprise Miner, Barry de Ville's Decision Trees for Business Intelligence and Data Mining illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and...
DATABASE MANAGEMENT SYSTEMS is designed for use in a course in databases. This book is distinctive in its emphasis on the practical side of databases. This means that it has unique coverage of database design, uses SQL throughout the book to demonstrate different concepts, and has an emphasis on query evaluation and optimization. In this revision...
Learn data structures and algorithms in Swift! Understanding how data structures and algorithms work in code is crucial for creating efficient and scalable apps. Swift’s Standard Library has a small set of general purpose collection types, yet they definitely don’t cover every case! In this book, you’ll learn how to...
Although traditional texts present isolated algorithms and data structures, they do not provide a unifying structure and offer little guidance on how to appropriately select among them. Furthermore, these texts furnish little, if any, source code and leave many of the more difficult aspects of the implementation as exercises. A fresh...
