Embarking on the adventure of natural language processing, my recent project aimed to tackle the challenge of sniffing out toxicity in sentences. Armed with a dataset I snagged from Kaggle, I set out to build a NLP model from scratch using tensorflow & keras. The main goal? Classifying sentences into distinct toxicity categories like TOXIC, SEVERE TOXIC, OBSCENE, INSULT, and IDENTITY HATE.
It’s not just about the code and algorithms – this project is a small step in making the online world a more pleasant place by sifting through and addressing various shades of unfriendly language. I must admit that the model I’ve been using isn’t quite powerful enough due to a shortage of resources, such as the dataset used and the computational power required for training the model.
Click the picture below to run the app.
For source code : Github
For dataset : Kaggle