DPDhairya Patelindhairya-ai-dev.hashnode.devยทNov 11, 2025 ยท 2 min readDay 17 โ Understanding Support Vector Machines (SVMs)Hey everyone ๐ Dhairya here, Today, I explored Support Vector Machines (SVMs) โ a powerful algorithm that can classify data by finding the best possible boundary between classes. After spending the last few days learning about ensemble methods and b...00
DPDhairya Patelindhairya-ai-dev.hashnode.devยทNov 10, 2025 ยท 2 min readDay 16 โ Gradient Boosting and XGBoostHey everyone ๐ Dhairya here, After exploring Random Forest and AdaBoost yesterday, today I took a deeper dive into Gradient Boosting and XGBoost โ algorithms that form the backbone of many Kaggle-winning solutions. These models are all about learnin...00
DPDhairya Patelindhairya-ai-dev.hashnode.devยทNov 9, 2025 ยท 2 min readDay 15 โ Ensemble Learning: Bagging, Random Forest & BoostingHey everyone ๐ Dhairya here, Iโm back after a long time took a break bacause of festive season and college exams and all i was unable to give time to learn and did not want to force things else i wont learn properly you know. After learning about hy...00
DPDhairya Patelindhairya-ai-dev.hashnode.devยทSep 15, 2025 ยท 2 min readDay 14 โ Hyperparameter Tuning with GridSearchCV & RandomizedSearchCVHey everyone ๐ Dhairya here, Today I took another big step in ML by learning hyperparameter tuning. After evaluating models with cross-validation, I realized that picking the right hyperparameters is just as important as choosing the model itself. ...00
DPDhairya Patelindhairya-ai-dev.hashnode.devยทSep 8, 2025 ยท 2 min readDay 13 โ Model Evaluation & Cross-ValidationHey everyone ๐ Dhairya here, After building my first ML models yesterday, I realized: training a model is easy, but properly evaluating it is the real challenge. Today, I focused on evaluation metrics and cross-validation to ensure that models are n...00