Mindforge ML | Unit 4 – Podcast 06_Title: Model Evaluation and Engineering Decisions

Building a model is only half the process — evaluating it correctly is critical.This episode explains performance metrics, confusion matrix analysis, bias–variance tradeoff and model comparison strategies.Key topics: Confusion Matrix: TP, TN, FP and FN interpretation. Performance Metrics: Accuracy, Precision, Recall and F1 Score. Overfitting vs Underfitting: Bias–variance understanding. Cross Validation: Reliable model assessment.This episode concludes Unit 4 and prepares the foundation for Unsupervised Learning.Series: Mindforge MLProduced by: Chatake Innoworks Pvt. Ltd.Initiative: MindforgeAI