Linear Regression Exercise

Programming for Data Science is a subject we’ve designed to explore the various programming components of data science.

Keywords

data science, data analysis, programming, dataidea

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Week 2: Linear Regression (3 Questions)

1. Linear Regression 1 Dimension

• Exercise: Implement a simple linear regression model to fit a line to 1D data points generated as (x, y) = (x, 3x + 7 + noise). Visualize the data and the fitted line.

2. Linear Regression with 1 Parameter

• Exercise: Create a linear regression model with a single parameter. Train the model on a dataset with a known linear relationship, and evaluate the model’s performance by plotting the predicted vs. actual values.

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3. Training Slope and Bias

• Exercise: Implement a linear regression model from scratch to learn the slope and bias for the dataset (x, y) = (x, 4x + 10 + noise). Compare the learned parameters with the true values.

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