Least Squares Regression

1. 1Import necessary libraries such as NumPy and scikit-learn
2. 2Prepare your dataset by defining features and target variables
3. 3Apply Linear Regression using Least Squares method
4. 4Evaluate model performance using metrics like Mean Squared Error
5. 5Visualize the line of best fit using matplotlib or seaborn

Data scientists and machine learning engineers can benefit from this method to improve model accuracy and make better predictions

💡 Least Squares Regression minimizes the sum of squares of residuals to find the best fit line

💡 Use Least Squares Regression to find the line of best fit for your data! #MachineLearning #DataScience