Day 17 – Understanding Support Vector Machines (SVMs)Support Vector Machines classify data by finding optimal boundaries, using kernels, and tuning hyperparameters for accurate predictions2 min read·dhairya-ai-dev.hashnode.devNov 11, 2025
Day 16 – Gradient Boosting and XGBoostGradient Boosting and XGBoost are powerful, optimized algorithms for reducing errors, known for speed and accuracy in machine learning competitions2 min read·dhairya-ai-dev.hashnode.devNov 10, 2025
Day 15 – Ensemble Learning: Bagging, Random Forest & BoostingLearn about ensemble learning techniques, including Bagging, Random Forest, and Boosting, to improve machine learning model performance2 min read·dhairya-ai-dev.hashnode.devNov 9, 2025
Day 14 – Hyperparameter Tuning with GridSearchCV & RandomizedSearchCVUse GridSearchCV and RandomizedSearchCV for hyperparameter tuning to optimize model accuracy and computation time2 min read·dhairya-ai-dev.hashnode.devSep 15, 2025
Day 13 – Model Evaluation & Cross-ValidationLearn the importance of model evaluation and cross-validation in machine learning with tips on metrics, train-test split, and confusion matrices2 min read·dhairya-ai-dev.hashnode.devSep 8, 2025