Capstone_Project_01_ML

Successfully completed the capstone project on Machine Learning algorithm.

Project Overview

In this capstone project, a machine learning model was developed using the students.csv dataset. Libraries such as Pandas and Sklearn were utilized. Data was extracted from MySQL , preprocessed, and used to create a logistic regression model. The data was split into training and testing sets, achieving an accuracy of 89% ✅.

Tools and Methodology

Tools

• 📊 Pandas: For data manipulation and preprocessing, ensuring clean and structured datasets for analysis.
• 📚 Sklearn: Used for building the logistic regression model and handling model training and testing.
• 💾 MySQL: Extracted the students.csv dataset from a MySQL database for further analysis.
• 🖥️ Jupyter Notebook: For interactive data analysis, visualization, and model development.

Methodology

• 🔍 Data Extraction: Retrieved the students.csv dataset from MySQL for analysis.
• 🧹 Data Preprocessing: Cleaned and prepared the data by handling missing values and standardizing features.
• 📈 Model Development: Built a logistic regression model to predict student outcomes based on the dataset.
• 🧪 Model Evaluation: Split data into training and testing sets, achieving an accuracy of 89% for validation.