akashkathole7/student_performance

Welcome to the Student Performance Prediction Project!

In this project, we will be using machine learning algorithms to predict the performance of students based on various factors such as their attendance, study time, and parental education level. Our goal is to build a system that can accurately predict the grades of students and help educators identify students who may need additional support.

Dependencies To run this project, you will need to install the following dependencies:

Python 3.6 or higher Scikit-learn Pandas Numpy Matplotlib Seaborn Don't worry if you don't have these dependencies installed, we have included a requirements.txt file that you can use to install them automatically.

Dataset The dataset used in this project is the Student Performance Dataset. It contains information about students, including their demographics, study habits, and exam grades.

Preprocessing Before we can train our model, we need to preprocess the data. This includes handling missing values and encoding categorical features. We will also perform some feature engineering to create new features that can improve the accuracy of our model.

Training We will train our model using the scikit-learn library's regression algorithms. This is a powerful algorithm that can handle both categorical and numerical features.

Testing To evaluate the accuracy of our model, we will use cross-validation and the accuracy metric. We will also generate a confusion matrix and a classification report to better understand the performance of our model.

Our program will preprocess the data, train the model, and test its accuracy. You can also modify the hyperparameters of the regression algorithm to see how it affects the accuracy of the model.

Conclusion With this project, we hope to have a better understanding of how machine learning algorithms can be used to predict the performance of students. We encourage educators to use this system to identify students who may need additional support and resources to succeed. Remember, education is the key to unlocking a brighter future!