BANA 7380-Advanced Business Analytics/BANA 6390-Big Data Analytics-Remidez: Podcasts, Newsletters, and Recommended Reading

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process.

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. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

nlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics. Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization- Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approachPython Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions.

If you are new to programming with Python and are looking for a solid introduction, this is the book for you. You will acquire the skills that you need for practical Python programming applications and will learn how these skills can be put to use in real-world scenarios. Throughout the chapters, you will find code samples that illustrate concepts presented. At the end of each chapter, you will find a complete game that demonstrates the key ideas in the chapter, a summary of the chapter, and a set of challenges that tests your newfound knowledge. By the time you finish this book, you'll be well versed in Python and be able to apply the basic programming principles you've learned to the next programming language you tackle.

R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.

Do Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story.