This is an end to end machine learning project to predict the score of the students based on parental level of education, ethnicity group and other several factors.
- Artifacts: In this folder preprocessed model pkl file, trained mode pkl file, raw data csv file, train data csv file, test data csv file are saved.
- Logs: These folder is dedicated for saving logging information.
- Notebook: In this folder basic eda and model training are perfomed.
- src: This is the source foldr which contains the following sub folders.
- Components: In this folder data collection, data transformation, and model training files are stored.
- Pipeline: In this folder predict pipeline and train pipeline files are stored.
- Exception.py: This file is responsible for exception handling.
- logger.py: This file is responsible for logging the necessary information.
- utils.py: This file is responsible for reuse of the code for repeatable tasks.
- Templates: In this folder we design the home page and prediction page.
- app.yaml: for web deployment using google cloud platform.
- main.py: to create web application using flask framework.
- requirements.txt: list of necessary dependencies to run the application.
- setup.py: code to install libraries listed in requirements.txt
- Clone the github repository by using the following link.
https://github.com/SaiSrinivas1997/Student_Score_Prediction.git
- Install the necessary dependencies usung the following command.
pip install -r requirements.txt- To run the application locally using flask execute the following command in the terminal and navigate to 127.0.0.1 in your browser.
python main.py- To deploy the application in google cloud platform edit your python version in app.yaml file and follow below procedure.
- Execute the below command and selct the configuration, mail and project.
gcloud init
- Now deploy the code using the following command and select the region.
gcloud app deploy app.yaml --project selected_project_name
- Navigate to the website by executing the following command.
gcloud app browse
when you navigated to the website add "/predictdata" at the end of the url to route to prediction page and select the one of the following options for the fields and click predict button to predict the score.
- Gender : Male/Female.
- Race or Ethnicity : Group A to E.
- Parental Level of Education : associate degree, bachelor degree, master degree, some college, some high school.
- Lunch type : standard, free/reduced.
- Test preparation score : none, completed.
- writing score : 0 to 100
- Reading score : 0 to 100
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