Name: Pavan Kalyan ID: cxipy2025091164 Duration: September 10 to October 31, 2025
I completed 3 tasks for this Python internship:
I made a program that reads CSV data and analyzes it. The program calculates averages and creates different charts like bar graphs, scatter plots, and heatmaps to visualize the data.
File: task1_data_analysis.py Output: data_analysis_visualizations.png
I built a machine learning model that predicts house prices. It looks at things like how many rooms a house has, the size, location, and age to estimate the price. I used Linear Regression for this.
The model worked pretty well with an R2 score of 0.9524 which means it's 95% accurate.
File: task2_house_prediction.py Output: house_price_prediction.png
I created a tool that does math operations on matrices. You can add matrices, multiply them, find the determinant, calculate inverse, and more. It has a demo mode that shows examples of all the operations.
File: task3_matrix_tool.py
First install the required libraries:
pip install pandas matplotlib seaborn numpy scikit-learn
Then run each program:
python task1_data_analysis.py python task2_house_prediction.py python task3_matrix_tool.py
For Task 3, choose option 2 for demo mode.
All the programs create their own sample data so you don't need to download anything extra. Just run them and they work.
The code includes comments explaining what each part does.