ML Model Training Training machine learning models involves selecting appropriate algorithms, preparing data, and optimizing model parameters to achieve strong predictive performance. Training Phases - Data Preparation : Cleaning, encoding, normalization - Feature Engineering : Creating meaningful features - Model Selection : Choosing appropriate algorithms - Hyperparameter Tuning : Optimizing model settings - Validation : Cross-validation and evaluation metrics - Deployment : Preparing models for production Common Algorithms - Regression : Linear, Ridge, Lasso, Random Forest - Classification…