Project 9 : Kaggle Natural Language Processing Competition — Part 1
Natural Language Processing with Disaster Tweets Classification part 1.
Sentiment analysis is the automated process of tagging data according to their sentiment, such as positive, negative and neutral. Sentiment analysis allows companies to analyze data at scale, detect insights and automate processes.
Introduction: Business Problem
Description: Sentiment analysis(Text classification) is a common task in the world of Natural Language Processing(NLP). The general idea is to take a phrase of text and determine if as we will explore in this Kaggle competition, whether the tweet indicates a disaster has occurred or if its just a regular tweet.
Evaluation: The evaluation metric for this competition is F1.
Methodology
The project will be executed by completing the following tasks:
- Notebook setup
- Data
- Tokenization
- Metrics
- Training
- Predictions
- Confusion Matrix
- Saving the model to huggingface
- Use the model via pipeline
