Regression Analysis/30_Days_of_Python

[pratikshabhujade]

Simple Regression Analysis

This Jupyter Notebook demonstrates simple regression techniques applied to stock data. It uses Python libraries to fetch stock data, prepare it, and apply linear regression models.

Features

• Data Fetching: Retrieve stock data from Yahoo Finance using yfinance.
• Data Preparation: Prepare data for regression analysis.
• Simple Linear Regression: Fit a linear regression model to predict stock prices.
• Model Evaluation: Assess model performance using metrics like MSE and R-squared.
• Visualization: Visualize actual vs. predicted prices and residuals.

Prerequisites

Install the required libraries: bash pip install yfinance matplotlib seaborn scikit-learn

Usage Clone the repository and install the dependencies. Open the Jupyter Notebook (Simple_Regression_Analysis.ipynb). Run the cells to fetch data, perform regression, and visualize results. Outputs Regression Plots: Visualize actual vs. predicted prices and residuals. Model Metrics: Evaluate the model using MSE and R-squared. Contributing Feel free to open issues or submit pull requests for improvements or additional features.

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[Shlokwankhade]

Go Ahead