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Course
- Data
Data Mining Algorithms in SSAS, Excel, and R
Don't use data mining as a black box. Get a deep understanding of how the data mining algorithms work. This knowledge is not only theoretical; it helps you developing better models in production.
What you'll learn
Data mining is gaining popularity as the most advanced data analysis technique. With modern data mining engines, products, and packages, like SQL Server Analysis Services (SSAS), Excel, and R, data mining has become a black box. It is possible to use data mining without knowing how it works. However, not knowing how the algorithms work might lead to many problems, including using the wrong algorithm for a task, misinterpretation of the results, and more. This course explains how the most popular data mining algorithms work, when to use which algorithm, and advantages and drawbacks of each algorithm as well. Demonstrations show the algorithms usage in SSAS, Excel, and R.
Table of contents
- Introduction and Modules | 2m 5s
- Assumptions and Overview | 53s
- What Is Data Mining? | 1m 34s
- Data Mining Types and Tasks | 2m 18s
- Demo: SQL Server Queries | 2m
- Demo: SSRS Report | 2m 23s
- Virtuous Cycle and CRISP Model | 1m 44s
- Data Flow | 1m 24s
- Types of Analyses and SQL Server Tools | 2m 12s
- Demo: SSAS Cube | 6m 37s
- Demo: Data Mining Model | 4m 52s
- Excel Tools and R | 2m 4s
- Summary | 50s
- Introduction | 30s
- Naive Bayes Prior | 2m 27s
- Naive Bayes Posterior | 2m 25s
- Example and Usage | 1m 31s
- Demo: Naive Bayes in SSAS | 4m 41s
- Demo: Naive Bayes in Excel | 3m 35s
- Demo: Naive Bayes in R | 5m 45s
- Decision Trees | 1m 59s
- Decision Trees Example | 1m 40s
- Decision Trees Example and Usage | 2m 40s
- Demo: Decision Trees in SSAS | 2m 56s
- Demo: Decision Trees in Excel | 2m 7s
- Demo: Decision Trees in R | 1m 44s
- Summary | 34s