Reddit Sentiment Analysis Using Deep Learning | 69% Accuracy Using TF-IDF | Python Project

🔍 Project Overview:

In this video, I demonstrate how to build a powerful Reddit Sentiment Analysis model using the Social Media Emotion Dataset, achieving up to 95% accuracy — all without using transformers like BERT!

✅ Techniques used:

Data Cleaning & Preprocessing

TF-IDF Vectorization (20,000 features)

Deep Neural Network (DNN) with Class Weights

Evaluation with Confusion Matrix & Classification Report

📂 Dataset: Social Media Emotion Dataset (from Kaggle)
📈 Model Accuracy: ~95%
🧠 Libraries Used: Scikit-learn, TensorFlow, Keras, NLTK, Pandas, Matplotlib

🎯 What You'll Learn:

How to preprocess Reddit-style comments for NLP

Apply TF-IDF + DNN for multi-class emotion classification

Handle class imbalance with class_weight

Evaluate model performance using accuracy and confusion matrix

Boost performance without transformers

💻 Code Available on GitHub: https://github.com/Tejaswini-M15/Reddit-Comment-Sentiment-Analysis-using-Deep-Learning
📊 Want to see a BERT version? Let me know in the comments!

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Видео Reddit Sentiment Analysis Using Deep Learning | 69% Accuracy Using TF-IDF | Python Project канала Tejaswini Mohapatra