ML Course Prep

A self-study repository to build Machine Learning foundations before starting formal coursework. Getting hands-on with Python, data tools, and ML concepts through practice notebooks and a final project.

Structure

• notebooks/ - Jupyter notebooks for each topic
• data/ - datasets used in exercises
• models/ - saved ML models
• app/ - final ML application (portfolio project)

Topics Covered

• NumPy & Pandas
• Data Visualization
• Scikit-learn
• Machine Learning Algorithms
• Model Evaluation

Tools & Libraries

• Python, NumPy, Pandas
• Matplotlib, Seaborn
• Scikit-learn
• Jupyter Notebooks