📚 ADL 202 Python and Statistical Modeling Lab Works (KTU)

Welcome to my repository of Jupyter Notebooks, where you'll find a collection of Python-based experiments, visualizations, and algorithms designed to learn, explore, and innovate.

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✨ Highlights

• 💡 Learn fundamental concepts through clear examples.
• 📈 Visualize data with creative plots and graphs.
• 🚀 Implement algorithms for sorting, traversal, and more.
• 🎯 Analyze statistical distributions and mathematical functions.

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🗂 Repository Contents

Notebook Name	Description
Bar Graph.ipynb	Create and customize bar graphs for data visualization.
Binomial Distribution.ipynb	Visualize and analyze the binomial distribution.
Frequency .ipynb	Explore frequency distributions and plotting.
Full Wave Rectifier.ipynb	Simulate and analyze the full wave rectifier circuit.
Graph of y=x^4+5.ipynb	Plot the graph of the polynomial function (y = x^4 + 5).
Histogram.ipynb	Create histograms to represent data distributions.
List Operations.ipynb	Perform various operations on Python lists.
List Traversal.ipynb	Demonstrate traversal techniques for Python lists.
Normal and Stem Graph.ipynb	Generate normal distributions and stem plots.
Poisson Distribution.ipynb	Visualize and analyze the Poisson distribution.
Replacing a Word in a Sentence.ipynb	Replace words in strings using Python.
String Traversal Methods.ipynb	Implement different string traversal techniques.
Bubblesort.ipynb	Implement the Bubble Sort algorithm for sorting.

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🚀 How to Get Started

1. Clone the Repository

   git clone https://github.com/shyamhari1074/<repository-name>.git

2. Navigate to the Repository

   cd <repository-name>

3. Open Jupyter Notebook

   jupyter notebook

4. Explore the Notebooks
   Select any .ipynb file and dive into learning!

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✨ Features

• Easy to Use: Notebooks are well-organized and beginner-friendly.
• Interactive Visualizations: Leverage Python libraries for engaging visuals.
• Hands-On Practice: Code examples included for practical understanding.
• Algorithms and Data: A mix of theoretical concepts and real-world applications.

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🐜 License

This repository is licensed under the MIT License. Feel free to use, modify, and share!

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🤝 Contributing

Contributions are always welcome!

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-branch).
3. Commit your changes (git commit -m "Add feature").
4. Push to the branch (git push origin feature-branch).
5. Open a Pull Request.

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📭 Contact

Feel free to reach out to me:

• GitHub: shyamhari1074
• LinkedIn: Shyam Hari

Let’s learn and grow together! 🎉

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