Python project on sentiment analysis using text vectorization with one-hot encoding and embedding

Predicted clinical status

1. The project develops a sentiment analysis model to classify text data into positive or negative sentiments, utilizing Python for preprocessing and model training.
2. Survival rate (0-1, with 1 being the best chance of survival).
3. This approach allows for capturing semantic relationships between words, improving the model's ability to interpret and analyze the sentiment of varied text inputs effectively.

Requirements

• Python 3
• NLTK - Natural Language Toolkit
• Pandas
• NumPy
• TensorFlow