Description
Ever wanted to do a Kaggle data science competition, but don’t know where to start?! This presentation is intended to meet the needs of data practitioners interested in getting started with predictive analytics and competitive data science. The presentation will describe the nature of competitive data science, and provide insights into the lessons learned by competing in several Kaggle competitions and achieving the expert competitor status. The presentation will provide a high level overview of Kaggle competitions, and the solution approaches that can be used to obtain top scores using Convolutional Neural networks (CNNs), random forests, and boosted trees. There will be a presentation followed by some time for questions.
Objectives:
- Understand the value of competitive data science as a tool to improve predictive analytics skills.
- Learn the basic hardware and software requirements to get started with machine learning problems.
Instructor's Bio
Maria Wellen
Senior Statistical Programmer at STATinMED
Maria Wellen is a Senior Statistical Programmer for STATinMED, a health economics outcomes research company. Maria has a Bachelor’s degree in Industrial Engineering from the Universidad Nacional de Colombia, a Masters degree in Statistics from the University of Kentucky and a credential as an Associate of the Society of Actuaries.
Local ODSC chapter in Austin, USA
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Learning from Kaggle
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