Augmentation
Type: Concept
As of November 2026, Augmentation has been mentioned in one podcast episode on Kaggle (Aug 2025). Technique used to enhance the training data for better model performance.
Data augmentation is a statistical technique which allows maximum likelihood estimation from incomplete data. Data augmentation has important applications in Bayesian analysis, and the technique is widely used in machine learning to reduce overfitting when training machine learning models, achieved by training models on several slightly-modified copies of existing data.
| Mentioned in | 1 episode on 1 podcast (as of November 2026) |
|---|---|
| First heard | Aug 2025 on Kaggle |
| Field | Data Science |
Who talks about Augmentation on podcasts?
Augmentation came up; the most recent mention was Aug 2025 on Kaggle.
What is Augmentation mentioned alongside?
Augmentation is most often mentioned alongside XGBoost, Applied Mathematics and Data Science.
Mentioned together: XGBoost, Applied Mathematics, Data Science, TF-IDF, Post-processing, Two-stage Modeling, Leaderboard, Ensemble Methods, Cross Validation, Feature Engineering