Participants will learn how to build effective machine learning models using different algorithms and evaluation techniques. The module explains model validation, performance metrics, overfitting prevention, hyperparameter tuning, and selecting the best model for business requirements.
Topics Covered
Supervised Learning
Unsupervised Learning
Classification Models
Regression Models
Clustering
Model Evaluation Metrics
Cross Validation
Hyperparameter Optimization
Bias and Variance
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