Practical Predictive Analytics

English | 2017 | ISBN: 978-1785886188 | 576 Pages | PDF, EPUB, AZW3 | 11 MB

Make sense of your data and predict the unpredictable
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.
What You Will Learn

• Master the core predictive analytics algorithm which are used today in business
• Learn to implement the six steps for a successful analytics project
• Classify the right algorithm for your requirements
• Use and apply predictive analytics to research problems in healthcare
• Implement predictive analytics to retain and acquire your customers
• Use text mining to understand unstructured data
• Develop models on your own PC or in Spark/Hadoop environments
• Implement predictive analytics products for customers