Python Libraries for AI/ML

🎯 Goal

📚 Libraries Covered

| Week | Library | Focus Area | Playlist Link | |------|----------|-------------|----------------| | 1️⃣ | NumPy | Numerical Computing | NumPy Playlist | | 2️⃣ | Pandas | Data Manipulation | Pandas Playlist | | 3️⃣ | Matplotlib | Data Visualization Basics | Matplotlib Video 1 | | 4️⃣ | Seaborn | Advanced Visualization | Seaborn Video 1 |

🗓️ Learning Plan (4 Weeks)

| Week | Focus | Topics | Deliverables | |------|--------|---------|--------------| | Week 1 | NumPy | Arrays, Indexing, Operations, Broadcasting | Notes, Notebooks, Practice Tasks | | Week 2 | Pandas | DataFrames, Filtering, GroupBy, Merging | Datasets, Code Examples | | Week 3 | Matplotlib | Plotting Basics & Advanced Visualizations | Graphs & Charts | | Week 4 | Seaborn | Advanced Data Visualization | Custom Plots, Style Control |

📂 Repository Structure

python-libraries-for-ai-ml/
│
├── 01_NumPy/
│   ├── Notes/
│   ├── Code/
│   └── README.md
│
├── 02_Pandas/
│   ├── Notes/
│   ├── Code/
│   └── README.md
│
├── 03_Matplotlib/
│   ├── Notes/
│   ├── Code/
│   └── README.md
│
├── 04_Seaborn/
│   ├── Notes/
│   ├── Code/
│   └── README.md
│
└── Summary/
    ├── Cheatsheets/
    ├── Practice_Tasks/
    └── Final_Revision.md

🧩 Tools & Technologies

• Language: Python 3.10+
• Environment: Jupyter Notebook / VS Code
• Libraries Used:

• Dataset Examples: CSV files, sample arrays, and visualization data

⚙️ Setup Instructions

• Clone this repository

git clone https://github.com/yourusername/python-libraries-for-ai-ml.git

• Install dependencies

pip install -r requirements.txt

• Open Jupyter Notebook

jupyter notebook

• Explore the notebooks inside each library folder.

📘 Learning Approach

• 🎥 Watch assigned YouTube playlist/videos daily
• 🧾 Take structured notes in the Notes/ folder
• 💻 Practice using Jupyter notebooks in Code/
• 📊 Apply visualization on real datasets in Datasets/

🧠 Key Learning Outcomes

By the end of this repository, you’ll be able to:

• Perform numerical computation with NumPy
• Conduct data analysis and cleaning using Pandas
• Build custom visualizations with Matplotlib
• Create statistical and AI-focused plots with Seaborn
• Understand how these libraries connect for AI/ML pipelines

🧾 Requirements

numpy
pandas
matplotlib
seaborn
jupyter

🏁 Progress Tracker

| Week | Library | Status | |------|----------|--------| | Week 1 | NumPy | ✅ Complete | | Week 2 | Pandas | ✅ Complete | | Week 3 | Matplotlib | ✅ Complete | | Week 4 | Seaborn | ✅ Complete |

👩‍💻 Developed by: Hamna Munir 🚀 Purpose: Building a strong Python foundation for AI/ML 📅 Duration: 4 Weeks