Using PyTorch Perform intent classification using three different models to see which one is better for this task

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Deep Learningnlp
Overview

DeepLearning---ATIS-dataset

In this notebook I will perform intent classification using three different models to see which one is better for this task. I will be using PyTorch. the data I used for this notebook is provided. The names are testlabel, testseq.in, train_label, trainseq.in

In this notebook you can expect to see:

  • Uploading the data and understanding it
  • Preprocessing the data and some feature engineering
  • Creating my own tokenization algorithm
  • Creating my own accuracy, confusion matrix and training functions
  • Feeding the data into the models and performing statistical inference

The models I used for intent classification are:

  • Simple ANN model
  • BiDirectional LSTM model based off of Yu Wang, Yilin Shen & Hongxia Jin
  • BERT transformer model (transfer learning). I used a pretrained model and changed it up a bit to work for my own problem.

I think Natural Language Processing is very interesting and hope to work on more similar projects.

Owner
Yoel Graumann
BSc in Statistics & Data Science
Yoel Graumann
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