Create data mining algorithmsAbout This BookDevelop a strong strategy to solve predictive modeling problems using the most popular data mining algorithmsReal-world case studies will take you from novice to intermediate to apply data mining techniquesDeploy cutting-edge sentiment analysis techniques to real-world social media data using RWho This Book Is ForThis Learning Path is for R developers who are lo...

A concise, hands-on guide with many practical examples and a detailed treatise on inference and social science research that will help you in mining data in the real world. Whether you are an undergraduate who wishes to get hands-on experience working with social data from the Web, a practitioner wishing to expand your competencies and learn unsupervised sentiment analysis, or you are simply interested in social data analysis, this book will prove to be an essential asset. No previous expe...

In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.With Beautiful Data, you will:Explore the opportunities and challenges involved in working with the vast number of datasets made available by the WebLearn...

Software Engineering and Object Oriented Modeling: This book is specially written for those who are interested in understanding software engineering and Object Oriented Modeling concepts using UML in the Computer Engineering and Information technology field and want to gain enhanced knowledge about the power of UML Language in software development.Also everyone with interest in learning UML for Software Engineering for application development can refer to this book to get the knowl...

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the...

In OBJECT THINKING, esteemed object technologist David West contends that the mindset makes the programmer—not the tools and techniques. Delving into the history, philosophy, and even politics of object-oriented programming, West reveals how the best programmers rely on analysis and conceptualization—on thinking—rather than formal process and methods. Both provocative and pragmatic, this book gives form to what’s primarily been an oral tradition among the field’s revolutionary thinkers—and...

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classificat...

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You’ll learn the steps necessary to create a successful machine-learning appl...

Object-Oriented Design with Applications has long been the essential reference to object-oriented technology, which, in turn, has evolved to join the mainstream of industrial-strength software development. In this third edition--the first revision in 13 years--readers can learn to apply object-oriented methods using new paradigms such as Java, the Unified Modeling Language (UML) 2.0, and .NET.The authors draw upon their rich and varied experience to offer improved ...

This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Py...

This book undertakes to marry the concepts of "Concept Mapping" with a "Design Thinking" approach in the context of business analysis. While in the past a lot of attention has been paid to the business process side, this book now focusses information quality and valuation, master data and hierarchy management, business rules automation and business semantics as examples for business innovation opportunities. The book shows how to take "Business Concept Maps" further as information models f...