Use Big Data and technology to uncover real-world insights You don't need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you'll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you'll develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get you stakeholder buy-in. Big Data has taken the marketplace by storm, and companies are seeking qualified talent to quickly fill positions to analyze the massive amount of data that are being collected each day. If you want to get in on the action and either learn or deepen your understanding of how to use predictive analytics to find real relationships between what you know and what you want to know, everything you need is a page away! The future starts today with the help of Predictive Analytics For Dummies .
Unfortunately, I did not find this book useful. When I first looked at the table of contents, I was excited about the potential content of the book, but I was disappointed after reading it. The algorithms and models commonly used in predictive analytics are not explained well in this book. For me, there are better books that cover this topic in a clearer, more readable, and enjoyable manner. I would highly recommend these two alternatives: Data Smart by John Foreman and Machine Learning with R by Brett Lantz.
I understand this is For Dummies series and the information should be plain and simple but not necessarily difficult to follow. I think this book could be written in half of its current size. There is an unnecessary amount of examples about what predictive analytics can be used for and yet it never felt like there was enough meat because methodologies used in such studies were never discussed in detail. On the contrary, if you are looking for something more technical, such as the last chapters of the book where you use Python and other data libraries, so you can get to the bone of the matter; it feels short and it looks more like cut-copy-paste style of teaching. It would have been more helpful if either part of the book was given a fair chance by splitting the book in two : Methods of Predictive Analytics vs. Predictive Analytics in Practice
A great overview of method for predicting analytics, including some of the tools that are available, and starting code for R and Python. I appreciated that the book included business-based reasons and arguments for using this technology, as well as a caution about personal privacy. A good introduction... or a good review.
This is the first book I've read that is dedicated to predictive analytics and its been fantastic. I realise its an introduction but I found it very wide ranging and had a good amount of detail to show the complexity of the topic while also making it accessible. This is a good place to start if you want to learn and predictive analytics
This entire review has been hidden because of spoilers.
Already having some experience working around predictive modelers and analytics in the FinServ industry as a business analyst and salesperson, I found this book to be a good introduction to the subject for anyone who needs a high level to semi technical understanding of the subject.