Exploratory Data Analysis: The Missing Ingredient for AI

Few things guarantee success with AI, but one thing guarantees failure: skipping exploratory data analysis. In this brand new, never before seen talk from AI practitioner and TrustInsights.ai Chief Data Scientist Christopher Penn, you’ll learn how to increase the odds of success for any AI project, whether with a vendor or in-house.

You’ll learn:

– What exploratory data analysis is and isn’t
– The negative consequences of skipping EDA
– Why AI demands proper EDA – and why so many companies skip this vital step
– How to conduct proper exploratory data analysis, from data integrity to feature selection to principal component analysis
– When to put the brakes on an AI project because your data isn’t ready

Most of this session is appropriate for any level practitioner; the walkthrough will showcase technologies in the free R programming language but does not require technical skill to understand.

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Exploratory Data Analysis: The Missing Ingredient for AI

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