$ Machine_Learning_Project█

> Developed a machine learning classification system in Python capable of distinguishing between walking and jumping motion patterns using processed input data and predictive modeling techniques.

> The project explored the end-to-end machine learning workflow, including data preprocessing, feature extraction, model training, and evaluation to better understand supervised learning concepts and classification accuracy.

• Built a supervised machine learning model in Python to classify movement patterns such as walking and jumping.
• Processed and analyzed input datasets using data manipulation and preprocessing techniques to improve model performance.
• Experimented with model training, testing, and evaluation workflows to compare prediction accuracy and classification effectiveness.
• Strengthened understanding of core machine learning concepts including feature engineering, classification algorithms, and dataset analysis.