🚫 Hate Speech Detection using Deep Learning As part of my Data Science learning journey, I developed a deep learning-based model to automatically detect hate speech in tweets.

🔍 Objective: To classify tweets into categories based on the presence of hate speech using natural language processing and LSTM-based deep learning.

🛠️ Tech Stack: Python, Pandas, NLTK, TensorFlow, Keras, LSTM, Regex

📌 Key Highlights:

Preprocessed tweet text by removing usernames, URLs, and HTML entities using regex and NLTK.

Tokenized and padded sequences for uniform input to the neural network.

Built an LSTM-based neural network using TensorFlow/Keras for sequence modeling.

Trained and evaluated the model on a labeled dataset with high accuracy.

✨ This project enhanced my skills in text preprocessing, deep learning for NLP, and model development for real-world classification problems.

📂 Dataset: Public dataset containing tweets labeled for hate speech