🤖 Machine Learning Zoomcamp

A collection of my hands-on exercises, notebooks, and projects completed during the Machine Learning Zoomcamp course.

This repository documents my learning journey through machine learning fundamentals, data preprocessing, model training, evaluation, and practical implementations using Python.

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📚 Course Topics

• Introduction to Machine Learning
• NumPy for Numerical Computing
• Linear Algebra Essentials
• Data Analysis with Pandas
• Machine Learning Fundamentals
• Linear Regression
• Model Validation
• Feature Engineering
• Model Evaluation
• Scikit-learn
• Practical Machine Learning Workflows

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📂 Repository Structure

Machine_Learning_Zoomcamp/
│
├── 01-intro/
│   ├── NumPy
│   ├── Linear Algebra
│   └── Pandas Exercises
│
├── 02-regression/
│   ├── Linear Regression
│   ├── Validation Framework
│   ├── Feature Engineering
│   └── Homework
│
├── requirements.txt
└── README.md

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🛠️ Technologies

• Python
• NumPy
• Pandas
• Scikit-learn
• Jupyter Notebook

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🎯 Learning Objectives

Throughout this course I am learning how to:

• Work with real-world datasets
• Clean and preprocess data
• Build Machine Learning models
• Evaluate model performance
• Apply Linear Regression algorithms
• Implement validation frameworks
• Follow industry-standard ML workflows

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📈 Progress

Module	Status
Introduction	✅ Completed
NumPy	✅ Completed
Linear Algebra	✅ Completed
Pandas	✅ Completed
Linear Regression	✅ Completed
Validation Framework	✅ Completed
More Modules	🚧 In Progress

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🚀 Repository Purpose

This repository serves as:

• My Machine Learning learning journal
• Practice notebooks and coding exercises
• Course assignments
• Portfolio showcasing my ML journey

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📌 Note

This repository will continue to be updated as I progress through the Machine Learning Zoomcamp course.

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⭐ If you find this repository useful, feel free to star it!