Machine Learning Journey

Hello, I'm Kavin 👋
I'm a BCA student learning Machine Learning with a strong focus on fundamentals, algorithms, and practical implementation.

This repository documents my step-by-step progress in Machine Learning, from data preprocessing to supervised and highlighting unsupervised learning models.

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📂 Repository Structure

1: Data Preprocessing

• Handling missing values
• Encoding categorical data
• Column Transformer
• Pipelines
• Train-test split

2: Supervised Learning

• Linear Regression
• Logistic Regression
• KNN
• Naive Bayes
• Decision Tree (with visualization)
• Random Forest

3: Unsupervised Learning

• K-Means Clustering
• Hierarchical Clustering
• DBSCAN Clustering

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Learning Approach

• Understand theory
• Implement using Python & scikit-learn
• Apply on real datasets
• Evaluate and analyze results

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Tools & Libraries

• Python
• NumPy, Pandas
• Matplotlib, Seaborn, plotly
• Scikit-learn

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This repository will be continuously updated as I progress further in ML & Deep Learning.