This repository contains all the experiments and projects performed during the AI and Data Science Lab course in the fifth semester of the B.Tech AI and Data Science program.
- Programming Languages: Python
- Tools: Git, Anaconda/Miniconda, VS Code, Jupyter Lab
- Python 3.8 or higher
- Install required packages:
pip install -r requirements.txtEach experiment is contained in its own directory with:
- Source code files (
.pyor.ipynb) - Dataset files or links
- Documentation/README specific to that experiment
- Results and outputs
Legend: ✅ Completed | 🔄 In Progress | ⏳ Planned
- Understanding of fundamental ML algorithms
- Hands-on experience with data preprocessing
- Implementation of various AI/ML models from scratch
- Data visualization and interpretation skills
- Project development and documentation practices
- Problem-solving using data-driven approaches
requirements.txt- Python dependencies.gitignore- Git ignore patterns
Detailed documentation for each experiment can be found in their respective directories. Each experiment includes:
- Problem statement and objectives
- Dataset description
- Implementation approach
- Results and analysis
- Conclusions and learnings
Student: [Your Name]
Roll Number: [Your Roll Number]
Course: B.Tech AI and Data Science
Semester: 5th
Institution: [Your Institution Name]
This project is licensed under the MIT License - see the LICENSE file for details.
- Course Instructor: [Instructor Name]
- Teaching Assistants
- Lab Coordinators
- Fellow students and study groups
Note: This repository is maintained as part of academic coursework. All experiments are performed for educational purposes and following academic integrity guidelines.