deck from Oredex - Machine Learning overview, also tools and process when integrated into Excel

1. Machine Learning
Smackdown
@LynnLangit

2. Agenda
Definitions
On premise solutions
3rd party Excel
Machine
Learning Add-ins
Microsoft SQL
Server Data
Mining Add-ins
R Studio
Cloud solutions
Predixion
Software
Azure
Machine
Learning

3. Analytics Defined
• Business Analytics - deterministic
 Query
 Aggregation
• Predictive Analytics - probabilistic
 Machine Learning
 Statistics
 Unsupervised Data Mining
 Supervised Data Mining
 Other

4. Machine Learning Roles Defined
Data Scientist
Store
Clean
Aggregate
ML Engineer
Selects
Libraries
Applies
Algorithms
Creates
Solutions
ML Researcher
Creates Algorithms

5. Algorithms by Example
 Segment – Cluster
 Example: Marketing
 Best Customer Traits
 Forecast – Time Series
 Example: Logistics
 Product movement over
time
 Classify/Estimate – Predict
 Example: Medical
 Predict condition
likelihood
 Associate – Market Basket
 Example: Retail
 Show these items nearby

6. ML Developer Learning Path Defined
Pick your
IDE
Learn a
ML
language
Pick a
problem
space
Get
Data
Visualize
results
Process
and
ITERATE

7. What is the R Language?

9. R Language Semantics
 search() and ls() # lists packages and objects in
scope
 ?mean # shows function definition
 Vectors (numeric, logical, character), lists, NULLs
 Data Frame, Matrix (same types), Factors (Categorical)
 meanx <- mean(x) or meanx = mean(x) # assignment
 x[1] <- 9 # extracts and/or changes pieces
 print(x) or x # prints x
 plot(x) # graphs x

10. 3rd party
Excel Machine Learning Add-ins
XLMiner StatsMiner XLStat RExcel
Important: All of these tools assume expert statistical knowledge

11. Add-in Example:
XLMiner

12. Data Mining Add-ins For Excel
Table Analysis Tools for Excel
•Use mining models with Excel
data or external data
Data Mining Client for Excel
•Create/test/explore/manage
Mining Models
Data Mining Templates for Visio
•Render/share mining models
as Visio Drawings
Important: Use requires connection to SQL Server 2012 SSAS

13. Data Mining Add-ins for Excel

14. Data Mining Structures
Containers
• Cleansed source data
One+ SSAS Algorithm(s)
• Clustering
• Time Series Prediction
• Market-Basket Analysis
• Text Mining
• Neural Networks
Models
• Query
• Model processing

16. Predixion Software

17. Predixion Software
Suite of tools for predictive analytics
Insight Now
Use mining models with Excel
data or external data
Insight
Analytics
Create/test/explore/manage
Mining Models
Insight
Workbench
Prepare data for model
creation
Web-based
Viewers and
Tools
HTML 5
Important: Runs as EITHER connected to SSAS on premise OR Connected to Predixion’s cloud-based servers

18. 18

19. Azure ML

20. Azure Machine Learning
Cloud-based
SaaS service
Create ML
Experiments
using Datasets
Can publish
results as Web
Services
Expects
knowledge of
statistics and
data mining

21. Understanding options…
Add-in
Server
Required
Complexity
of install
Other
Cost of
Add-in
Cost of
Solution
XLMiner none easy Assumes stats expertise $$ $$
RExcel none easy Assumes R expertise $ $
Data Mining Add-ins SQL Server SSAS medium Designed for single user 0 $$$
Predixion on premise SQL Express easy Requires local R install 0 $$-$$$
Predixion on premise SQL Server SSAS medium Your data is stored locally 0 $$$$
Predixion cloud none easy Supports SSAS Data Mining
AND R Language
0 $$-$$$
Azure Machine
Learning
none easy Rich set of algorithms and
supports R
n/a unknown

22. @LynnLangit