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# Emotion Classification with Neural Networks | ||
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## Overview | ||
This project focuses on classifying emotions using neural networks. The goal is to build a model that can accurately predict emotions based on input data, utilizing various techniques in machine learning and deep learning. | ||
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## Features | ||
- Implementation of different neural network architectures for emotion classification. | ||
- Data preprocessing techniques to prepare the dataset. | ||
- Performance evaluation metrics to assess model accuracy. | ||
- Visualizations to illustrate results and model performance. | ||
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## Technologies Used | ||
- Python | ||
- TensorFlow / Keras | ||
- NumPy | ||
- Pandas | ||
- Matplotlib / Seaborn | ||
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## Installation | ||
To get started with this project, follow these steps: | ||
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1. Clone the repository: | ||
```bash | ||
git clone https://github.com/Pranshu-jais/ML-Nexus.git | ||
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<img width="570" alt="Screenshot 2024-10-06 110414" src="https://github.com/user-attachments/assets/390518c1-4c6a-4156-a2eb-371dba23264c"> |