Book Image

Practical Predictive Analytics

By : Ralph Winters
Book Image

Practical Predictive Analytics

By: Ralph Winters

Overview of this book

This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

About the Reviewers

Armando Fandango serves as chief technology officer of REAL Inc., building AI-based products and platforms for making smart connections between brands, agencies, publishers, and audiences. Armando founded NeuraSights with the goal of creating insights from small and big data using neural networks and machine learning. Previously, as chief data scientist and chief technology officer (CTO) for Epic Engineering and Consulting Group LLC, Armando worked with government agencies and large private organizations to build smart products by incorporating machine learning, big data engineering, enterprise data repositories, and enterprise dashboards. Armando has led data science and engineering teams as head of data for Sonobi Inc., driving big data and predictive analytics technology and strategy for JetStream, Sonobi's AdTech platform. Armando has managed high-performance computing (HPC) consulting and infrastructure for the Advanced Research Computing Centre at UCF. Armando has also been advising high-tech startups Quantfarm, Cortxia Foundation, and Studyrite as an advisory board member and AI expert. Armando has authored a book titled Python Data Analysis - Second Edition and has published research in international journals and conferences.

 

Alberto Boschetti is a data scientist, with strong expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he daily faces challenges spanning among natural language processing (NLP), machine learning, and distributed processing. He is very passionate about his job and he always tries to be updated on the latest developments in data science technologies, attending meetups, conferences, and other events. He is the author of Python Data Science Essentials, Regression Analysis with Python and Large Scale Machine Learning with Python, all published by Packt.