【独家发布】Practical Predictive Analytics

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1. Practical Predictive Analytics
   
2. Authors: Ralph Winters
   
3. ISBN-10 书号: 1785886185
   
4. ISBN-13 书号: 9781785886188
   
5. Release 出版日期: 2017-07-06
   
6. pages 页数: (357)
   
7. 49.99
   
8. 
   
9. Book Description
   
10. Key Features
    
11. A unique book that focuses on developing practical skills to make informed business decisions using predictive analytics
    
12. Apply the principles and techniques of predictive analytics to effectively interpret big data
    
13. Solve real-world analytical problems with the help of practical case studies and real-world scenarios
    
14. Book Description
    
15. This is a go-to book for anyone interested in predicting actions of people, businesses, and more. With this book, you will learn the entire process of predictive analytics and modeling techniques to practically implement them.
    
16. 
    
17. You’ll get started with the basics of predictive analytics and its applications along with the installation and set up of the tools. Once you have completed the installation, get ready for an exciting journey to uncover answers to hidden questions. You will learn about entering the data (or should I say dirty data), cleaning the data, and apply modeling techniques to this data. When you have done the crucial bit and cleaned the data, we’ll tell you stories from within and let you visit the future.
    
18. 
    
19. “You” – the fortune teller now can predict the number of expected re-admissions in a hospital or even the place where a virus may hit next. Wouldn’t it be great if you could predict the injury and insurance claim payments based on the characteristics of the insured’s vehicle or predict load defaults? Are you going to acquire those 10k customers for your start-up? Build your own model and answer this crucial question yourselves in the later part of the book.
    
20. 
    
21. The journey does not end here, and you will learn to present your results with fantastic visualizations to showcase your results to the world. By the end of this book, you’ll have learned about, implemented, and mastered predictive analytic techniques.
    
22. 
    
23. What you will learn
    
24. Find out how predictive analytics work
    
25. Identify, model, and prioritize the decisions you need to optimize
    
26. Classify the right algorithm for your requirements
    
27. Use and apply predictive analytics to research problems in healthcare
    
28. Implement predictive analytics to retain and acquire your customers
    
29. Use text mining to understand unstructured data
    
30. Contents
    
31. Chapter 1. Getting Started with Predictive Analytics
    
32. Chapter 2. The Modeling Process
    
33. Chapter 3. Inputting and Exploring Data
    
34. Chapter 4. Introduction to Regression Algorithms
    
35. Chapter 5. Introduction to Decision Trees, Clustering, and SVM
    
36. Chapter 6. Using Survival Analysis to Predict and Analyze Customer Churn
    
37. Chapter 7. Using Market Basket Analysis as a Recommender Engine
    
38. Chapter 8. Exploring Health Care Enrollment Data as a Time Series
    
39. Chapter 9. Introduction to Spark Using R
    
40. Chapter 10. Exploring Large Datasets Using Spark
    
41. Chapter 11. Spark Machine Learning – Regression and Cluster Models
    
42. Chapter 12. Spark Models – Rule-Based Learning

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Practical Predictive Analytics