Update README.md

README.md

@@ -7,7 +7,36 @@ sdk: gradio
 sdk_version: 4.37.2
 app_file: app.py
 pinned: false
-license: apache-2.0
+license: mit
 ---
+# Twitter Sentiment Analysis
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+This project implements a sentiment analysis model to predict the sentiment (positive or negative) of tweets. An LSTM-based model has been trained on 1.6 million tweets.
+
+## Project Structure
+
+- __01. Data Preparation:__
+  * `Data Collection`: The dataset consisting 1.6 million tweets has been collected from [here](https://www.kaggle.com/datasets/kazanova/sentiment140).
+  * `Data Cleaning & Preprocessing`:
+    - Removed stopwords
+    - Applied Lemmatization
+    - Vectorized the lemmatized data utilizing "TextVectorization" from keras
+    - Saved the Vectorizer for utilizing later in the app
+  
+- __02. Model Training:__
+  * A Bidirectional LSTM model with an embedding layer has been trained on the preprocessed data.
+  
+- __03. App Deployment:__
+  * Developed a web-app with Gradio interface
+  * Deployed the [App](https://huggingface.co/spaces/mazed/twitter_sentiment_analysis) in HuggingFace Spaces
+
+- `requirements.txt`: Contains the dependencies needed for the project:
+  - `pandas`
+  - `tensorflow==2.15.0`
+  - `nltk`
+  - `gradio`
+
+
+
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference