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Mastering Predictive Analytics with R
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.
Mastering Predictive Analytics with R
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced...
R: Predictive Analysis
Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naive Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alik...
Mastering Predictive Analytics with R - Second Edition
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential conceptsAbout This Book* Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding* Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types* Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easilyWho This Book Is ForAlthough budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced...
Mastering Predictive Analytics with R
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced...
Learning Bayesian Models with R
Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book Understand the principles of Bayesian Inference with less mathematical equations Learn state-of-the art Machine Learning methods Familiarize yourself with the recent advances in Deep Learning and Big Data frameworks with this step-by-step guide Who This Book Is For This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications. ...
Reimagining Businesses with AI
Discover what AI can do for your business with this approachable and comprehensive resource Reimagining Businesses with AI acquaints readers with both the business challenges and opportunities presented by the rapid growth and progress of artificial intelligence. The accomplished authors and digital executives of the book provide you with a multi-industry approach to understanding the intersection of AI and business. The book walks you through the process of recognizing and capitalizing on AI’s potential for your own business. The authors describe: How to build a technological foundation that allows for the rapid implementation of artificial intelligence How to manage the disruptive nature of powerful technology while simultaneously harnessing its capabilities The ethical implications and security and privacy concerns raised by the spread of AI Perfect for business executives and managers who seek a jargon-free and approachable manual on how to implement artificial intelligence in everyday operations, Reimagining Businesses with AI also belongs on the bookshelves of anyone curious about the interaction between artificial intelligence and business.
