Custom SGD (Stochastic) Implementation for Linear Regression on Boston House Dataset
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Custom SGD (Stochastic) Implementation for Linear Regression on Boston House Dataset

ByKishore

In this post, we’ll explore the implementation of Stochastic Gradient Descent (SGD) for Linear Regression on the Boston House dataset. We’ll compare our custom implementation with the SGD implementation provided by the popular machine learning library, scikit-learn. Importing Libraries Data Loading and Preprocessing We load the Boston House dataset, standardize the data, and split it…

Understanding Bagging and Random Forest Models

Understanding Bagging and Random Forest Models

ByKishore

Ensemble methods are powerful techniques that combine multiple weak learners to improve predictive performance. One popular ensemble method is bagging, which aggregates the predictions of multiple models trained on subsamples of the data. Random Forest, a widely used algorithm, employs bagging with decision trees to produce robust and scalable models. Introduction In this blog post,…