Quality Assurance and Project Management

Aug 30 2019   2:30PM GMT

Predictive Analytics and Data Mining @Amazon

Jaideep Khanduja Jaideep Khanduja Profile: Jaideep Khanduja

Tags:
Amazon
Data Mining
Predictive Analytics

Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner by Vijay Kotu and Bala Deshpande

Book Excerpt as on Amazon.com:

Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand the conceptual framework and immediately practice the concepts learned using the open-source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. You’ll be able to: 1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general-purpose analytics process. 2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases. 3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open-source GUI based data mining tool

Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density-based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com

Demystifies data mining concepts with easy to understand language
Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis
Explains the process of using open source RapidMiner tools
Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics
Includes practical use cases and examples

“If learning-by-doing is your mantra — as well it should be for predictive analytics — this book will jumpstart your practice. Covering a broad, foundational collection of techniques, authors Kotu and Deshpande deliver crystal-clear explanations of the analytical methods that empower organizations to learn from data. After each concept, screenshots make the ‘how to’ immediately concrete, revealing the steps needed to set things up and go; you’re guided through real hands-on execution.”

–Eric Siegel, Ph.D., founder of Predictive Analytics World and author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

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