machine learning 101: basic of making sense of data (supervised) & values
Post on 02-Jul-2015
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akeM oveL 101Basic of Making a Genius Baby (Supervised) & Benefits
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What if 100,000 or more feeds/activities everyday?
Share of Voices
Categories
Improve Accuracy - Parameters: Gaussian, Multinomial, Bernoulli... - Techniques: ensembling, boosting, bagging...
- Data: Clean, Volume, Features...
Summary
Basic of Making Sense of Data (Supervised) & Values
achineM earningL 101
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