A clean, beginner-friendly hub of ML practice notebooks, templates, notes, and infographics.

📝 Description

This repository is my personal machine learning study space.

It now includes:

• 🧪 Practice exercises from beginner-friendly ML courses
• 📘 Notes I’m writing while learning (NEW — now adding full notes section)
• 🧱 ML templates for quick model building (NEW)
• 🖼️ Visual infographics made using NotebookLM
• 🗂️ Clean folder structure for easy revision

Everything is written in an easy, beginner-first style.

📂 What’s Inside

✔️ Practice Notebooks

Covers beginner-level ML topics:

• Data preprocessing
• Exploratory data analysis
• Linear regression
• Logistic regression
• Basic classification
• Clustering fundamentals
• Simple NLP tasks
• Evaluation basics

(Everything kept simple — no heavy math or deep learning yet.)

✔️ ML Templates (NEW)

Reusable "starter templates" for quick ML projects.

Current templates include:

📌 Linear Regression Template
📌 Data Preprocessing Template
📌 Train–Test Split Template
📌 Model Evaluation Template
📌 Categorical Encoding Template

Each template includes:

• Clean structure
• Explanations inside
• Editable cells
• Ready-to-run workflow

Perfect for practicing the same pipeline on multiple datasets.

✨ Contributors

blu3-bird 💻 📖 🤔 🖋

XLEB 💻 📖

Sindhu 📖

Abhishek Yadav 📖

✔️ Learning Notes (NEW)

A new section dedicated to handwritten-style ML notes.

Planned notes include:

• Data Cleaning Basics
• Handling Missing Values
• Encoding Techniques
• Train/Test/Validation
• Linear Regression (Full Breakdown)
• Evaluation Metrics Explained

These notes are short, easy, and beginner-friendly — ideal for revision.

✔️ Visual Infographics

NotebookLM-generated visuals to make concepts easier to remember.

Examples include:

• Regression flow
• Normalization vs Standardization
• Types of ML
• Bias vs Variance

🎯 Purpose of This Repo

This repo helps me:

• Learn ML step-by-step
• Practice on real datasets
• Reuse templates for multiple models
• Keep all notes, experiments, and visuals organized
• Build confidence with hands-on learning

Ideal for absolute beginners trying to understand ML slowly.

🔮 Future Plans

• More ML templates
• More structured notes
• Better folder classification
• Mini ML projects:
  • House price regression
  • Simple classification tasks
  • Customer segmentation
• More infographics

🤝 Contributing

Contributions are welcome and appreciated!
Please read our CONTRIBUTING.md to get started.

It contains:

• Contribution workflow
• Branch & commit guidelines
• AI usage policy
• PR & issue standards

⭐ Support

If this repo helps you, hit that star ⭐
It keeps me motivated to learn more every day.