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Explore:

🔴What is the Objective of Linear Regression?
🔴What best fit means?
🔴Final Optimization Problem?
🔴Linear Regression Regularization term?
🔴Loss Function and Loss Minimization Perspetive of Linear Regression?
🔴Special Point of Linear Regression!!

Points:

1. Decision Surface
2. Assumptions
3. Feature Importance & Model Interpretability
4. If data is Imbalance
5. If data contains outliers
6. How to solve for outliers
7. If data have missing values

Explore Industry-Grade Pipelines and Solutions

This is a framework for handling imbalanced datasets provides industry-grade pipelines and solutions to help you overcome the challenges of imbalanced data and improve the performance of your machine learning models

Points:

1. Identify Imbalanced Datasets
2. Address the Imbalance
3. Evaluate the results