Python for Data Science Learning 📊🐍

Welcome to Python for Data Science Learning! This repository is a collection of Jupyter notebooks and Python files documenting my learning of Python for data science. Here, I explore various Python libraries, techniques, and concepts related to data analysis and visualization. It reflects my progress, challenges, and the knowledge I've gained as I move towards mastering data science, with a future goal of diving into machine learning.

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📌 About This Repository

This repository serves as:

• A showcase of my learning journey in Python for data science.
• A resource for others starting their data science journey.
• A personal archive of projects, practice notebooks, and solved exercises.
• A preparation step for future explorations into machine learning.

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🗂️ Repository Structure

The repository is organized into folders files and notebooks based on specific topics or libraries:

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🧰 Tools and Libraries

This repository uses the following Python libraries and tools:

• NumPy: For numerical computing and array manipulations.
• Pandas: For data manipulation and analysis.
• Matplotlib: For basic data visualization.
• Seaborn: For advanced visualizations.
• Jupyter Notebook: For interactive code writing and analysis.

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✨ Features

• Beginner to intermediate-level notebooks and python code files with examples and explanations.
• Focus on practical data science concepts like:
  • Data cleaning
  • Exploratory data analysis (EDA)
  • Data visualization
• Hands-on projects to apply learned concepts.
• Continuous updates as I practice and learn.

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📅 Learning Goals

My main objectives with this repository are:

1. To build a strong foundation in Python for data science.
2. To explore real-world datasets and derive insights from them.
3. To prepare for machine learning by mastering data science basics.

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🚀 Future Plans

Once I solidify my data science skills, I plan to:

• Explore machine learning algorithms.
• Work on predictive modelling projects.
• Dive into deep learning and artificial intelligence.

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🤝 Contributing

If you're also learning Python for data science and want to contribute:

1. Fork the repository.
2. Add your own notebooks or suggest improvements.
3. Create a pull request, and I’ll review it.

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📧 Contact

Feel free to reach out for questions, collaboration, or feedback:

• Email: [email protected]

Let’s grow and learn together! 🚀