Applied-Natural-Language-Processing Solution

$30.00 $26.40

Description

  1. In this task, you will be im-plementing a sequence-to-sequence Recursive Neural Network (RNN) model in TensorFlow.You will be using the same data from the HMM Coding Assignment 3 for Part-of-Speechtagging

  1. In this assignment you will write a naive Bayes classifier to identify hotel reviews as either truthful or deceptive, and either positive or negative. You will be using the word tokens as features for classification. The assignment will be graded based on the performance of your classifiers, that is how well they perform on unseen test data compared to the performance of a reference classifier.

  1. In this assignment you will write perceptron classifiers (vanilla and averaged) to identify hotel reviews as either truthful or deceptive, and either positive or negative. You may use the word tokens as features, or any other features you can devise from the text. The assignment will be graded based on the performance of your classifiers, that is how well they perform on unseen test data compared to the performance of a reference classifier.

  1. In this assignment you will write a Hidden Markov Model part-of-speech tagger for Italian, Japanese, and a surprise language. The training data are provided tokenized and tagged; the test data will be provided tokenized, and your tagger will add the tags. The assignment will be graded based on the performance of your tagger, that is how well it performs on unseen test data compared to the performance of a reference tagger.