Tagged “talks”
- Advanced Data Preparation for Supervised Machine Learning
- Preparing Messy Data For Supervised Learning (Python)
- Practical Data Science with R
- Myths of Data Science: Things You Should and Should Not Believe
- Improving Prediction using Nested Models and Simulated Out-of-Sample Data
- Statistically Validate Models with R
- Validating Models in R
- An Introduction to Differential Privacy as Applied to Machine Learning
- Prepping Data for Analysis Using R
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