vidhi1290 / emotion-classifier-with-deep-learning

Welcome to the Emotion Classifier project! This repository contains a comprehensive solution for emotion classification using Natural Language Processing (NLP) and deep learning techniques.😭🤣🙂

Emotion Classifier with Deep Learning 🚀

Welcome to the Emotion Classifier project! This repository contains a comprehensive solution for emotion classification using Natural Language Processing (NLP) and deep learning techniques.

Overview

This project aims to build a model capable of accurately categorizing text samples into three emotion classes: anger, joy, and fear. The provided dataset, "Emotion_classify_Data.csv," forms the basis for training and evaluating our model.

Emotion Classifier with Deep Learning 🚀

Index 📖

1. Introduction
2. Dataset Overview
3. Data Preprocessing
   1. Loading the Dataset
   2. Data Cleaning and Label Encoding
   3. Train-Test Split
4. Tokenization and Padding
5. Model Architecture
6. Model Training
7. Model Evaluation
8. Visualizations
   1. Training History
   2. Confusion Matrix
9. Actual vs. Predicted Examples
10. Conclusion

1. Introduction 🚀

Welcome to the Emotion Classifier journey! Our mission? Unleash the power of NLP and deep learning to decode emotions from text.

2. Dataset Overview 📊

Our dataset, named "Emotion_classify_Data.csv," is a treasure trove of emotions—anger, joy, and fear—spread across 5937 entries.

3. Data Preprocessing 🧹

3.1. Loading the Dataset

Let’s open the treasure chest and explore the dataset structure.

3.2. Data Cleaning and Label Encoding

Transforming text into numbers—our magical preprocessing step.

3.3. Train-Test Split

Balance is key! We split the dataset into realms of training and testing.

4. Tokenization and Padding 📝

Turning text into sequences and ensuring a uniform length for our magical machine.

5. Model Architecture 🏰

Our emotion classification castle: an embedding layer, an LSTM tower, and a dense layer with softmax magic.

6. Model Training 🚂

Witness the model’s evolution over 10 enchanting epochs.

7. Model Evaluation 🌟

The grand reveal! Classification metrics paint a vivid picture of our model’s emotional insight.

8. Visualizations 📈

8.1. Training History

A visual symphony of accuracy and validation accuracy dancing over epochs.

8.2. Confusion Matrix

A heatmap spectacle revealing the model’s performance in vivid colors.

9. Actual vs. Predicted Examples 🎭

The stage is set! Ten examples showcasing the model’s prowess in predicting emotions.

10. Conclusion 🌟

In this magical journey, we’ve crafted a robust solution for emotion classification. The model, a beacon of performance, awaits those delving into the enchanting world of NLP.

Connect with Me 🌐

• LinkedIn: Vidhi Waghela
• Kaggle: Vidhi Kishor Waghela
• GitHub: Vidhi1290
• Email: [email protected]

🚀 Open to Collaborations and Tech Discussions!