AIML NLP Project - Ticket Classification

The goal is to build a classifier that can classify the tickets by analyzing text. Pre-Processing, Data Visualization and EDA ● Exploring the given Data files ● Understanding the structure of data ● Missing points in data ● Finding inconsistencies in the data ● Visualizing different patterns ● Visualizing different text features ● Dealing with missing values ● Text preprocessing ● Creating word vocabulary from the corpus of report text data ● Creating tokens as required Model Building  Building a model architecture which can classify.  Trying different model architectures by researching state of the art for similar tasks.  Train the model  To deal with large training time, save the weights so that you can use them when training the model for the second time without starting from scratch. Test the Model, Fine-tuning and Repeat ● Test the model and report as per evaluation metrics ● Try different models ● Try different evaluation metrics ● Set different hyper parameters, by trying different optimizers, loss functions, epochs, learning rate, batch size, checkpointing, early stopping etc..for these models to fine-tune them ● Report evaluation metrics for these models along with your observation on how changing different hyper parameters leads to change in the final evaluation metric.