@PatelDhairya

Day 17 – Understanding Support Vector Machines (SVMs)

Nov 11, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today, I explored Support Vector Machines (SVMs) — 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...

Day 16 – Gradient Boosting and XGBoost

Nov 10, 2025 · 2 min read · Hey everyone 👋 Dhairya here, After exploring Random Forest and AdaBoost yesterday, today I took a deeper dive into Gradient Boosting and XGBoost — algorithms that form the backbone of many Kaggle-winning solutions. These models are all about learnin...

Day 15 – Ensemble Learning: Bagging, Random Forest & Boosting

Nov 9, 2025 · 2 min read · Hey everyone 👋 Dhairya here, I’m 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...

Day 14 – Hyperparameter Tuning with GridSearchCV & RandomizedSearchCV

Sep 15, 2025 · 2 min read · Hey everyone 👋 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. ...

Day 13 – Model Evaluation & Cross-Validation

Sep 8, 2025 · 2 min read · Hey everyone 👋 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...