- Analysis of KNN algorithm in terms of under/over fitting and train/test error.
- Implementing Bootstrap method on a dataset using KNN (K=10), and understanding the relationship between uncertainty and number of datasets from bootstrapping.
- Implementation of Stochastic and Batch Gradient Descent Algorithms and their relationships.
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- Analysis of KNN algorithm in terms of uncertainty, under/over fitting and train/test error.
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