https://github.com/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.😭🤣🙂
https://github.com/vidhi1290/emotion-classifier-with-deep-learning
confusion-matrix emotion-classifier emotion-detection lstm lstm-neural-networks nlp nlp-machine-learning softmax visualization
Last synced: 23 days ago
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Welcome to the Emotion Classifier project! This repository contains a comprehensive solution for emotion classification using Natural Language Processing (NLP) and deep learning techniques.😭🤣🙂
- Host: GitHub
- URL: https://github.com/vidhi1290/emotion-classifier-with-deep-learning
- Owner: Vidhi1290
- Created: 2023-11-16T08:02:52.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-16T11:02:36.000Z (almost 2 years ago)
- Last Synced: 2025-03-28T17:49:54.511Z (6 months ago)
- Topics: confusion-matrix, emotion-classifier, emotion-detection, lstm, lstm-neural-networks, nlp, nlp-machine-learning, softmax, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 56.6 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 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](#1-introduction)
2. [Dataset Overview](#2-dataset-overview)
3. [Data Preprocessing](#3-data-preprocessing)
1. [Loading the Dataset](#31-loading-the-dataset)
2. [Data Cleaning and Label Encoding](#32-data-cleaning-and-label-encoding)
3. [Train-Test Split](#33-train-test-split)
4. [Tokenization and Padding](#4-tokenization-and-padding)
5. [Model Architecture](#5-model-architecture)
6. [Model Training](#6-model-training)
7. [Model Evaluation](#7-model-evaluation)
8. [Visualizations](#8-visualizations)
1. [Training History](#81-training-history)
2. [Confusion Matrix](#82-confusion-matrix)
9. [Actual vs. Predicted Examples](#9-actual-vs-predicted-examples)
10. [Conclusion](#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](https://www.linkedin.com/in/vidhi-waghela-434663198/)
- **Kaggle:** [Vidhi Kishor Waghela](https://www.kaggle.com/vidhikishorwaghela)
- **GitHub:** [Vidhi1290](https://github.com/Vidhi1290)
- **Email:** [vidhiwaghela99@gmail.com](mailto:vidhiwaghela99@gmail.com)
🚀 **Open to Collaborations and Tech Discussions!**