Welcome to the AI/ML Assignment repository! This repository contains Python assignments focused on Data Science, Machine Learning, and Artificial Intelligence concepts using popular libraries like NumPy and Pandas.
This repository contains assignment solutions with their corresponding question papers.
| File Name | Description |
|---|---|
Assignment_01.ipynb |
First assignment - Python basics |
Mid_assignment.ipynb |
Mid-term assignment solutions |
Python for ML Mid Term.pdf |
Mid-term exam question paper |
employees.csv |
Auto-generated dataset for analysis |
README.md |
This documentation file |
First assignment covering fundamental Python programming concepts:
- Filter Operations: Working with lambda functions and filters to extract even numbers from lists
- Data Manipulation: Basic Python data structure operations
- Interactive Programming: Input/output handling in Python
Mid-term assignment focusing on data analysis with NumPy and Pandas.
📄 View Question Paper: Python for ML Mid Term.pdf
This notebook contains solutions to all questions from the mid-term examination.
- Array creation and properties (dtype, ndim, shape, size)
- Statistical operations (max, min, mean)
- Array filtering and boolean indexing
- Element-wise operations
- Aggregate functions (sum, difference calculations)
- DataFrame operations (head, tail, info, describe)
- Data selection and slicing
- Filtering data by conditions
- Sorting operations
- Data modification and updates
- Working with CSV files
Dataset: Employee data containing:
- ID
- Age
- Salary
- Department (HR, IT, Finance, Sales)
Make sure you have Python installed (Python 3.7+ recommended) along with the following libraries:
pip install numpy pandas jupyter- Clone this repository:
git clone https://github.com/Jami40/AI_ML_Assignment.git
cd AI_ML_Assignment- Launch Jupyter Notebook:
jupyter notebook- Open any of the
.ipynbfiles to view and run the assignments
Simple Python operations demonstrating:
- List comprehensions
- Lambda functions
- Filter operations
- User input handling
Mid Assignment (Question Paper PDF)
Comprehensive data analysis assignment covering:
NumPy Tasks:
- Extract age and salary arrays from CSV data
- Calculate statistics (max, min, average)
- Filter employees by age criteria
- Perform array transformations
- Calculate aggregates
Pandas Tasks: 6. Load and explore employee dataset 7. Select specific columns and rows 8. Filter by department 9. Sort by salary (descending) 10. Update salary values and recalculate averages
- Understanding NumPy array operations and properties
- Working with Pandas DataFrames
- Data filtering and selection techniques
- Statistical analysis using Python
- CSV file handling
- Data transformation and manipulation
- Python 3.x: Core programming language
- NumPy: Numerical computing library
- Pandas: Data analysis and manipulation library
- Jupyter Notebook: Interactive development environment
Email: jnjami40@gmail.com
This repository is for educational purposes as part of AI/ML coursework.
This is an assignment repository, but suggestions and improvements are welcome! Feel free to:
- Fork the repository
- Create your feature branch
- Submit a pull request
Note: The employees.csv file is generated automatically when running the Mid Assignment notebook. Make sure to run the data generation cell first before attempting other questions.
- ✅ Assignment 01 - Completed
- ✅ Mid Assignment - Completed
Happy Learning! 🎓