A Best Practices Cookbook for Data Mining [AAI-299-P]
Speaker(s):
Mark Tabladillo
Artus Krohn-Grimberghe
Duration: full day
Track: Advanced Analytics and Insights
Data mining increasingly fascinates business people and information technology professionals alike, with the promise of finding meaningful patterns, relationships, and opportunities in our continuously growing volumes of data. There are tried and tested best practices you can follow to begin and improve your data mining efforts. You’re invited to a full-day data mining seminar with Mark Tabladillo and Artus Krohn-Grimberghe to see these best practices in action. Aimed at the beginning to intermediate data scientist, this pre-conference workshop builds on Mark and Artus’ experience in teaching university students and advising industry clients. Following a cookbook theme for their presentation, they will be explaining and demonstrating their best practices framework by cooking through a data science example from beginning to end, covering these topics:
• How to avoid mythology while establishing a data science investigation
• How to apply the best artistry in data cleansing and transformation (shaping)
• How to apply best practices for machine learning algorithms
• How to communicate your data mining story within and beyond your organization
The presenters have designed specific breaks during the workshop where you can discuss and interact with them and other attendees. Note that these best practices transcend Microsoft SQL Server Data Mining, applying equally to other software, such as Matlab, Octave, R, SAS, SPSS, and Weka. After this workshop, you and your data science team will have the knowledge and best practices to approach small to large data mining challenges with confidence.
Accompanying Materials:
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