https://github.com/khushi130404/placemetrix
A machine learning-based placement prediction app using IQ and CQPA as inputs. Built with Python in Jupyter Notebook, leveraging scikit-learn, pandas, and matplotlib.
https://github.com/khushi130404/placemetrix
jupyter-notebook machine-learning matplotlib python scikit-learn
Last synced: 2 months ago
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A machine learning-based placement prediction app using IQ and CQPA as inputs. Built with Python in Jupyter Notebook, leveraging scikit-learn, pandas, and matplotlib.
- Host: GitHub
- URL: https://github.com/khushi130404/placemetrix
- Owner: Khushi130404
- License: mit
- Created: 2024-12-17T07:32:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-18T03:32:17.000Z (over 1 year ago)
- Last Synced: 2025-03-01T13:23:48.787Z (over 1 year ago)
- Topics: jupyter-notebook, machine-learning, matplotlib, python, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 154 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Security: SECURITY.md
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README
# Placemetrix
Placemetrix is a placement prediction application designed to predict placement outcomes based on IQ (Intelligence Quotient) and CQPA (Cumulative Quality Point Average). The project leverages machine learning models to analyze and predict whether a candidate is likely to get placed.
## Features
Placement Prediction: Input IQ and CQPA to predict placement outcomes.
Data Visualization: Visualize data distributions and model performance using Matplotlib.
User-Friendly: Simple and straightforward implementation in a Jupyter Notebook.
## Built With
Python: Core programming language for development.
Jupyter Notebook: Interactive environment for code and visualization.
## Libraries Used:
scikit-learn: For machine learning model development and evaluation.
Matplotlib: For visualizing data and results.
Pandas: For data manipulation and preprocessing.
NumPy: For numerical computations.