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Deep Dive into Regression and Classification Metrics

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Overview

This course provides an in-depth understanding of evaluation metrics for both regression and classification models. By the end of this course, you will be able to evaluate the performance of your machine learning models properly in different scenarios.

Syllabus

Unit 1: Understanding MSE, MAE, RMSE and Their Differences

Changing RMSE to MAE Calculation
Calculating House Price Errors
Compare MSE and MAE effects
Complete the Linear Regression Code and Calculate MAE

Unit 2: R-squared Metric

Update Predictions for R-Squared Calculation
Calculating R-squared for House Prices
Compare R-sqared to MSE

Unit 3: Classification Metrics

Confusion Matrix Values in Spam Classification
Calculate Precision and Recall
Calculate Accuracy for Email Classification
Calculate Classification Metrics
Compute Confusion Matrix and F1-Score

Unit 4: Building and Understanding AUC-ROC

Calculating TPR and FPR
Calculate AUC-ROC for Medical Test
Calculating AUC-ROC for Medical Diagnosis
ROC Curve Plotting and AUC Calculation

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