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.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
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+# Flask stuff:
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+
+# Jupyter Notebook
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+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.artifacts/
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+ENV/
+env.bak/
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+# Spyder project settings
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+# Rope project settings
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+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
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+# Pyre type checker
+.pyre/
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+# pytype static type analyzer
+.pytype/
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+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

Dockerfile

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+FROM python:3.9
+
+## set the working directory to /code
+WORKDIR /code
+
+## Copy the current directory contents in the container at /code
+COPY ./requirements.txt /code/requirements.txt
+
+## Install the requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Set up a new user named "user" 
+RUN useradd user
+# Switch to the "user" user
+USER user
+
+# Set home to the user's home directory
+
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+## Start the FASTAPI App on port 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

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----
-title: StudentExamPerformancePrediction
-emoji: 📈
-colorFrom: yellow
-colorTo: yellow
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Student-Exam-Performance-Prediction
+emoji: 💬
+colorFrom: purple
+colorTo: blue
+sdk: streamlit
+sdk_version: "1.38.0"
+app_file: src/app.py
+pinned: false
+---
+
+End Two Mchine learining Project 

app.py

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+# Importing necessary modules from Flask to create the web application
+from flask import Flask, request, render_template
+
+# Importing additional necessary libraries
+import numpy as np  # For numerical operations
+import pandas as pd  # For data manipulation and creating DataFrame objects
+
+# Importing custom modules: CustomData and PredictPipeline from the 'src.pipeline.predict_pipeline' module
+from src.pipeline.predict_pipeline import CustomData, PredictPipeline
+
+# Initializing the Flask application
+app = Flask(__name__)
+
+# Defining the route for the homepage of the web application
+@app.route('/')
+def index():
+    # Rendering the 'index.html' template when the root URL is accessed
+    return render_template('home.html')
+
+# Defining the route for prediction, with both GET and POST methods allowed
+@app.route('/predictdata', methods=['GET', 'POST'])
+def predict_datapoint():
+    # If the request method is GET, render 'home.html'
+    if request.method == 'GET':
+        return render_template('home.html')
+    else:
+        try:
+            # Capture the form data (ensure form field names match these keys)
+            data = CustomData(
+                gender=request.form.get('gender'),
+                race_ethnicity=request.form.get('ethnicity'),
+                parental_level_of_education=request.form.get('parental_level_of_education'),
+                lunch=request.form.get('lunch'),
+                test_preparation_course=request.form.get('test_preparation_course'),
+                reading_score=float(request.form.get('reading_score')),  # Ensuring correct casting
+                writing_score=float(request.form.get('writing_score'))   # Ensuring correct casting
+            )
+
+            # Convert the collected form data into a pandas DataFrame
+            pred_df = data.get_data_as_data_frame()
+            print(f"Input DataFrame: \n{pred_df}")
+
+            # Initialize the prediction pipeline
+            predict_pipeline = PredictPipeline()
+
+            # Make the prediction
+            results = predict_pipeline.predict(pred_df)
+            print(f"Prediction Result: {results}")
+
+            # Render 'home.html' and display the prediction result
+            return render_template('home.html', results=results[0])
+
+        except Exception as e:
+            print(f"Error during prediction: {e}")
+            # If any error occurs, render the home page with an error message
+            return render_template('home.html', error="An error occurred during prediction. Please check your input.")
+
+# Run the Flask app
+if __name__ == "__main__":
+    # Running the app on host 0.0.0.0 (accessible from any device in the network), debug mode ON for development
+    app.run(host="0.0.0.0", debug=True)

requirements.txt

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+pandas
+numpy
+seaborn
+matplotlib
+scikit-learn
+catboost
+xgboost
+Flask
+

setup.py

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+from setuptools import find_packages, setup
+from typing import List
+
+HYPEN_E_DOT = '-e .'
+
+def get_requirements(file_path: str) -> List[str]:
+    '''
+    This function will return the list of requirements
+    '''
+    requirements = []
+    with open(file_path) as file_obj:
+        requirements = file_obj.readlines()
+        requirements = [req.replace("\n", "") for req in requirements]
+
+        if HYPEN_E_DOT in requirements:
+            requirements.remove(HYPEN_E_DOT)
+
+    return requirements
+
+setup(
+    name="student-exam-performance-prediction",
+    version="1.0.0",
+    packages=find_packages(),
+    # Package metadata
+    author="Suresh Beekhani",
+    author_email="sureshbeekhani26@gmail.com",
+    description="A tool for predicting student exam performance based on various factors.",
+    long_description="This package provides a comprehensive model for predicting student exam performance using data analysis and machine learning techniques.",
+    long_description_content_type="text/markdown",
+    url="https://github.com/SURESHBEEKHANI/Student-Exam-Performance-Prediction.git",
+    # Read dependencies from requirements.txt
+    install_requires=get_requirements('requirements.txt'),
+    # License and classification
+    license="MIT",
+    classifiers=[
+        "Programming Language :: Python :: 3.12",
+        "License :: OSI Approved :: MIT License",
+        "Operating System :: OS Independent",
+    ],
+)