This repo contains Logistic Regression project where I take random 1000 students records from different universities This repo will predict chance of a student Pass/Back based on academic & lifestyle factors
Records of 1000 random student records:
- study_hour , sleep_hour
- class_attendence, study_AM/PM
- internet_access, exam_score
- pass/back
- Source: https://www.kaggle.com/datasets/kundanbedmutha/exam-score-prediction-dataset (kaggle site)
- Format : 1000 students record on 7 parameters
- Target feature: Pass/Back
- Import Python packages & Datasets
- Exploratory Data Analysis (EDA)
- Graphs & Charts
- Distribution of Exam level
- Sleep hours impact on result
- Night study vs performence vs internet access
- Features Engineering
- Train the Model
- Train_Test_Split
- accuracy
- confusion metrix
- classification report & Cross Validation
- python
- pandas
- numpy
- matplotlib
- seaborn
- sklearn
- git clone https://github.com/Lakhan-cs/Logistic-Regression.git (On terminal)
- pip install -r requirements.txt (essential packages on bash commond)
- cd "Lakhan-cs/Linear-reg_project" (Access the repo file can also modify the repo.)