Merge pull request #1728 from anandpiyush1521/master

Student Place Prediction

Author: avinashkranjan

Student-placement-prediction/.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
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
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+# Sphinx documentation
+docs/_build/
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+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# 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.
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+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
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+#Pipfile.lock
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+#   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
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+
+# 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/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
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+# Celery stuff
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+*.sage.py
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+# Environments
+.env
+.venv
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+ENV/
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+# mkdocs documentation
+/site
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+.mypy_cache/
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+# PyCharm
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+#  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/

Student-placement-prediction/README.md

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+# Student Placement Prediction
+
+[![forthebadge](https://forthebadge.com/images/badges/made-with-python.svg)](https://forthebadge.com)
+
+<h2>Table of Contents</h2>
+<ul>
+    <li>Project Overview</li>
+    <li>Installation</li>
+    <li>Usage</li>
+    <li>Features</li>
+    <li>Technologies Used</li>
+
+
+</ul>
+
+<h2 >Project Overview</h2>
+<p>
+    This project is aimed at developing a web application that predicts the placement status of students based on various parameters. It utilizes the Python programming language and the Flask web framework to provide an
+    interactive and user-friendly interface.
+</p>
+
+<h2 >Installation</h2>
+<ol>
+    <li>Clone the repository:
+        <pre><code>git clone https://github.com/your-username/student-placement-prediction.git</code></pre>
+    </li>
+    <li>Change into the project directory:
+        <pre><code>cd student-placement-prediction</code></pre>
+    </li>
+    <li>Create a virtual environment:
+        <pre><code>python3 -m venv env</code></pre>
+    </li>
+    <li>Activate the virtual environment:
+        <pre><code>source env/bin/activate</code></pre>
+    </li>
+    <li>Install the project dependencies:
+        <pre><code>pip install -r requirements.txt</code></pre>
+    </li>
+    <li>Run the Flask application:
+        <pre><code>python app.py</code></pre>
+    </li>
+    <li>Open your web browser and visit <a href="http://localhost:5000">http://localhost:5000</a> to access the
+        application.</li>
+</ol>
+
+<h2 >Usage</h2>
+<p>
+    Upon accessing the web application, you will be presented with a user interface where you can enter the necessary
+    details for prediction. Fill in the required fields, such as academic scores, skills, and personal information.
+    Click on the "Predict" button to submit the form and receive the predicted placement status.
+</p>
+
+<h2 >Features</h2>
+<ul>
+    <li>Predicts the placement status of students based on input parameters</li>
+    <li>User-friendly web interface for input and result display</li>
+    <li>Handles various input data formats and provides appropriate error messages</li>
+    <li>Interactive and responsive design for easy usage on different devices</li>
+</ul>
+
+<h2 >Technologies Used</h2>
+<ul>
+    <li>Python: Programming language used for the backend development and machine learning algorithms.</li>
+    <li>Flask: Web framework used for building the web application.</li>
+    <li>HTML/CSS: Markup and styling languages for creating the user interface.</li>
+    <li>Bootstrap: CSS framework for responsive and visually appealing design.</li>
+    <li>Machine Learning Libraries: Python libraries such as scikit-learn, pandas, and numpy used for data
+        processing, model training, and prediction.</li>
+</ul>
+
+
+winscp - with help of this we can upload our file on aws
+
+putty - it is a remote client, we take access of machine through ssh. Can open EC2's command prompt in putty
+
+sudo apt-get update && sudo apt-get install python3-pip
+
+pip install -r requirements.txt
+
+screen -R deployment python3 app.py
+
+AWS deployment - Amazon EC2 => ec2-52-15-92-145.us-east-2.compute.amazonaws.com

Student-placement-prediction/app.py

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+from flask import Flask, render_template, request
+import pickle
+import numpy as np
+
+model = pickle.load(open('model.pkl', 'rb'))
+app = Flask(__name__)
+
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+
+@app.route('/predict', methods=['POST'])
+def predict_placement():
+    cgpa = float(request.form.get('cgpa'))
+    iq = int(request.form.get('iq'))
+    profile_score = int(request.form.get('profile_score'))
+
+    result = model.predict(np.array([cgpa, iq, profile_score]).reshape(1, 3))
+
+    if result[0] == 1:
+        result = 'Placed'
+    else:
+        result = 'Not placed'
+
+    return render_template('index.html', result=result)
+
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', port=8080)
+

Student-placement-prediction/model.pkl

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+flask
+numpy
+sklearn