This repository contains a collection of beginner-to-intermediate level machine learning notebooks developed using Python and Jupyter Notebooks. These projects focus on applying Linear Regression, Logistic Regression, and Classification techniques to real-world datasets.
| Notebook | Description |
|---|---|
| FlowerSpeciesLRCM.ipynb | Classifies different flower species using Logistic Regression and Confusion Matrix. |
| ScorePredictionUsingLRRM.ipynb | Predicts student scores based on study hours using Linear Regression and Residual Metrics. |
| TransmissionLineFaultDetectionAndClassification.ipynb | Detects and classifies faults in transmission lines using signal analysis techniques. |
| basic.ipynb | A basic practice notebook for quick prototyping and ML concept testing. |
ScoresPrediction.csv: Used in the student score prediction model.
- Python (NumPy, Pandas, Matplotlib, Scikit-learn)
- Jupyter Notebooks
- Linear Regression & Logistic Regression
- Confusion Matrix & Error Metrics
Created with 💡 by Abhishek Agrawal