AI Learning Repository

Welcome to the AI Learning Repository!
This repository is a growing collection of resources, code snippets, and experiments related to Artificial Intelligence (AI), starting with Python, NumPy, Pandas, and Visualization. More topics and libraries will be added soon.

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📚 Contents

1. Python Basics
2. NumPy for Numerical Computing
3. Pandas for Data Manipulation
4. Data Visualization & Encoding
5. More Coming Soon...

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1. Python Basics

This section covers:

• Variables, Data Types, and Operators
• Control Structures (if, for, while)
• Functions and Modules,Class
• Working with Libraries

📘 Notebook: Python.ipynb

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2. NumPy for Numerical Computing

This section covers:

• Creating and manipulating arrays
• Array broadcasting and vectorization
• Indexing and slicing
• Mathematical operations
• Linear algebra operations
• Random number generation

📘 Notebook: Numpy.ipynb

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3. Pandas for Data Manipulation

This section will include:

• Reading data from CSV, Excel, JSON, etc.
• DataFrames and Series
• Data cleaning and preprocessing
• Grouping and aggregation
• Merging and joining datasets

📘 Notebook: pandas.ipynb

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4. Data Visualization & Encoding

This section will include:

• Plotting with Matplotlib and Seaborn
• Exploratory Data Analysis (EDA)
• Handling categorical variables
• One-hot and label encoding

📘 Notebook: visualization_and_encoding.ipynb

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More Coming Soon...

Planned additions:

• 🧠 Scikit-learn for machine learning
• 🧮 SymPy for symbolic computation
• 🤖 TensorFlow / PyTorch for deep learning

Stay tuned!

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💡 How to Use

1. Clone the repository:

   git clone https://github.com/yourusername/ai-learning.git