Linear Regression from Scratch with Code
📰 Medium · Machine Learning
Learn to implement Linear Regression from scratch using Closed Form Solution and Gradient Descent, understanding the intuition and mathematics behind it
Action Steps
- Implement Linear Regression using Closed Form Solution
- Apply Gradient Descent to optimize the model
- Compare the results of both methods
- Visualize the regression line using a library like Matplotlib
- Test the model with a sample dataset
Who Needs to Know This
Data scientists and machine learning engineers can benefit from this article to improve their understanding of Linear Regression and implement it in their projects
Key Insight
💡 Linear Regression can be implemented using both Closed Form Solution and Gradient Descent, each with its own advantages and disadvantages
Share This
Implement Linear Regression from scratch using Closed Form Solution and Gradient Descent! #MachineLearning #LinearRegression
Key Takeaways
Learn to implement Linear Regression from scratch using Closed Form Solution and Gradient Descent, understanding the intuition and mathematics behind it
Full Article
Understanding the intuition, mathematics, and implementation behind Linear Regression using Closed Form Solution and Gradient Descent. Continue reading on Medium »
DeepCamp AI