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🚀 Edunet Foundation Internship Projects

Python Jupyter Scikit Learn Pandas NumPy

Edunet Foundation × UpSkill Campus Internship

Domain: Data Science & Machine Learning


📖 About

This repository contains the projects completed during the Edunet Foundation Internship Program conducted in collaboration with UpSkill Campus.

Throughout the internship, I worked on real-world Machine Learning projects involving:

  • Data Preprocessing
  • Exploratory Data Analysis (EDA)
  • Feature Engineering
  • Machine Learning Model Development
  • Model Evaluation
  • Data Visualization
  • GitHub Project Documentation

📂 Repository Structure

upskillcampus/
│
├── README.md
├── Internship_Report.pdf
│
├── Project-1-Crop-Yield-Prediction/
│
└── Project-2-Smart-City-Traffic-Pattern-Forecasting/

🌾 Project 1 — Crop Yield Prediction using Machine Learning

📌 Objective

Predict agricultural crop yield using machine learning algorithms based on historical crop data.

Technologies Used

  • Python
  • Jupyter Notebook
  • Pandas
  • NumPy
  • Matplotlib
  • Scikit-learn
  • Joblib

Workflow

  • Dataset Exploration
  • Data Cleaning
  • Exploratory Data Analysis (EDA)
  • Feature Selection
  • Linear Regression
  • Decision Tree Regressor
  • Model Evaluation
  • Model Saving

Evaluation Metrics

  • Mean Absolute Error (MAE)
  • Mean Squared Error (MSE)
  • R² Score

🚦 Project 2 — Smart City Traffic Pattern Forecasting

📌 Objective

Forecast future traffic volume using historical traffic data and Machine Learning techniques.

Technologies Used

  • Python
  • Jupyter Notebook
  • Pandas
  • NumPy
  • Matplotlib
  • Scikit-learn

Workflow

  • Data Cleaning
  • Feature Engineering
  • Date-Time Processing
  • Random Forest Regression
  • Model Evaluation
  • Traffic Prediction
  • Data Visualization

Evaluation Metrics

  • MAE
  • MSE
  • RMSE
  • R² Score

🛠️ Technologies Used

  • Python
  • Jupyter Notebook
  • Pandas
  • NumPy
  • Matplotlib
  • Scikit-learn
  • Joblib
  • Git & GitHub

🎯 Internship Learning Outcomes

During this internship I gained practical experience in:

  • Machine Learning Workflow
  • Data Cleaning & Preprocessing
  • Feature Engineering
  • Regression Algorithms
  • Model Evaluation
  • Data Visualization
  • GitHub Version Control
  • Technical Documentation

📁 Included Documents

  • Internship Report
  • Project Source Code
  • Jupyter Notebooks
  • Datasets
  • Requirements Files
  • Project Documentation

👨‍💻 Author

Fardeen Akmal

Final Year B.E. Computer Engineering (IoT, Cyber Security & Blockchain Technology)

📧 Email: fardeenakmal123@gmail.com

🔗 GitHub: https://github.com/fardeenakmal

🔗 LinkedIn: https://www.linkedin.com/in/fardeenakmal


📜 Internship

Organization: Edunet Foundation

Training Partner: UpSkill Campus

Domain: Data Science & Machine Learning


⭐ Acknowledgements

I would like to thank Edunet Foundation and UpSkill Campus for providing this internship opportunity, enabling me to gain practical experience in Data Science and Machine Learning through real-world projects.


⭐ If you found this repository useful, please consider giving it a Star!

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