Global Data Science Forum

How to Fare Well in Machine Learning Competitions 

Wed November 28, 2018 06:51 PM

"This session will introduce Kaggle machine learning competition platform, and describe an effective methodology to fare well on it, developed by a Kaggle Grand Master. The methodology covers data exploratory analysis, feature engineering, model evaluation, and algorithm tuning. Machine learning competitions are a simplified version of real-world machine learning, and we will discuss additional steps that need to be added to the methodology."

This webcast was produced by Jean Francois Puget, Distinguished Engineer at IBM.

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