PALLAVI UMAKANT WAGHMARE
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Comparing Ensemble Learning Benchmarks: Random Forest vs Gradient Boosting vs XGBoost Model/Algorithms
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Random Forest primarily reduces variance by training multiple decision trees independently on different bootstrap samples and combining their predictions. This makes the model more stable and less sensitive to…
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Supervised Learning: Comparing 5 Machine Learning Algorithms on a Real Dataset
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A practical comparison of five supervised learning algorithms—Logistic Regression, Decision Tree, KNN, SVM, and Naive Bayes—trained on the same real-world dataset and evaluated using consistent preprocessing and classification metrics.
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What I Learned by Building Linear Regression from Scratch with NumPy
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A practical look at what I learned while building Linear Regression from scratch using NumPy, including data preparation, Gradient Descent, model evaluation, and comparison with Scikit-Learn during my internship…