In this tutrial we will understand different techniques of classification on text data.

1. Learn the hardware challenges and requirements
2. Objective is to learn deep learning techniques for nlp classification models(binal, multiclass and multi-label)
3. Try models on multiple datasets (we can start tweet disaster but finally it on walmart data)
4. Standard EDA/feature engineering required for NLP projects
5. Data transformation, so that models can consume inputs
6. Theory of corresponding models and nitty-gritties