| Author |
Bari, Anasse,
|
| Series |
For dummies |
|
--For dummies.
|
| Subject |
Management -- Data processing.
|
|
Management -- Mathematical models.
|
|
Data mining.
|
|
Data Mining
|
| Alt Name |
Chaouchi, Mohamed,
|
|
Jung, Tommy,
|
| Description |
1 online resource |
| Note |
Print version record. |
| Summary |
Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big DataPredictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businessesHelps readers see how to shepherd predictive analytics projects through their companiesExplains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and moreCovers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing dataAlso covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewherePropose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies. |
| Contents |
Introduction. -- pt. 1. Getting started with predictive analytics. Entering the arena ; Predictive analytics in the wild ; Exploring your data types and associated techniques ; Complexities of data -- pt. 2. Incorporating algorithms in your models. Applying models ; Identifying similarities in data ; Predicting the future using data classification -- pt. 3. Developing a roadmap. Convincing your management to adopt predictive analytics ; Preparing data ; Building a predictive model ; Visualization of analytical results -- pt. 4. Programming predictive analytics. Creating basic prediction examples ; Creating basic examples of unsupervised predictions ; Predictive modeling with R ; Avoiding analysis traps ; Targeting big data -- pt. 5. The part of tens. Ten reasons to implement predictive analytics ; Ten steps to build a predictive analytic model. |
| ISBN |
9781118729205 (electronic bk.) |
|
111872920X (electronic bk.) |
|
9781118729410 (electronic bk.) |
|
1118729412 (electronic bk.) |
|
1118728963 |
|
9781118728963 |
|
9781118728963 |
| Publisher # |
EB00057970 Recorded Books |
| OCLC # |
864560209 |
| Additional Format |
Print version: Bari, Anasse. Predictive analytics for dummies. Hoboken, N.J. : John Wiley & Sons, 2013 9781118729410 |
|
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