Title of the Publication

Author: Saral Cynthiya M
Date: September 2025

---

Abstract

Provide a concise summary of your research or project.
Example:
This study explores the application of AI-powered data visualization for improving decision-making in cloud-based systems. Key contributions include dataset preprocessing, deep learning integration, and real-time visualization dashboards.

---

Methodology

1. Data Collection

   • Source: Kaggle Dataset
   • Preprocessing: Normalization, feature selection, missing value handling.

2. Model Development

   • Frameworks: PyTorch, TensorFlow, or Scikit-learn
   • Model: Neural Network with dropout layers for regularization.

3. Evaluation Metrics

   • Accuracy, Precision, Recall, F1-score.
   • Visualization via Matplotlib & Seaborn.

# Example code snippet
import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [2, 4, 6])
plt.title("Sample Graph")
plt.show()

<!-- RT_DIVIDER -->
# Methodology
# Title of the Publication
_Author: Saral Cynthiya M_  
_Date: September 2025_

---

## Abstract
Provide a concise summary of your research or project.  
Example:  
This study explores the application of **AI-powered data visualization** for improving decision-making in cloud-based systems. Key contributions include dataset preprocessing, deep learning integration, and real-time visualization dashboards.

---

## Methodology
1. **Data Collection**  
   - Source: [Kaggle Dataset](https://www.kaggle.com/)  
   - Preprocessing: Normalization, feature selection, missing value handling.

2. **Model Development**  
   - Frameworks: PyTorch, TensorFlow, or Scikit-learn  
   - Model: Neural Network with dropout layers for regularization.

3. **Evaluation Metrics**  
   - Accuracy, Precision, Recall, F1-score.  
   - Visualization via Matplotlib & Seaborn.

```python
# Example code snippet
import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [2, 4, 6])
plt.title("Sample Graph")
plt.show()
<!-- RT_DIVIDER -->
# Results
# Title of the Publication
_Author: Saral Cynthiya M_  
_Date: September 2025_

---

## Abstract
Provide a concise summary of your research or project.  
Example:  
This study explores the application of **AI-powered data visualization** for improving decision-making in cloud-based systems. Key contributions include dataset preprocessing, deep learning integration, and real-time visualization dashboards.

---

## Methodology
1. **Data Collection**  
   - Source: [Kaggle Dataset](https://www.kaggle.com/)  
   - Preprocessing: Normalization, feature selection, missing value handling.

2. **Model Development**  
   - Frameworks: PyTorch, TensorFlow, or Scikit-learn  
   - Model: Neural Network with dropout layers for regularization.

3. **Evaluation Metrics**  
   - Accuracy, Precision, Recall, F1-score.  
   - Visualization via Matplotlib & Seaborn.

```python
# Example code snippet
import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [2, 4, 6])
plt.title("Sample Graph")
plt.show()