Score: Full mark + all bonus
Grade: A+
This repository stores all project codes from said course, titled 'Machine Learning with Natural Language Processing'
Project 1 is about Naive Bayes. It requires students to compute Naive Bayes prior, likelihood and posterior probabilities. Used codes are attached as well. See Proj1/proj1_q.pdf for more information.
Project 2 is about Sentimental Analysis of text. Students are required to train their best models and compete with one another in kaggle. In this project, different methods are attempted.
NaiveBayes.ipynb: Code I adapted from sample codes, which used native numpy codes writing a Naive Bayes classifier.NaiveBayes-sklearn.ipynb: Naive Bayes classifier with sklearn library.sklearn-MLP.ipynb: Multilayer Perceptron classifier using sklearn library.ModelEnsemble.ipynb: An ensemble model combining Naive Bayes, Logistic Regression (notebook lost during development) and MLP.Tensorflow.ipynb: A quick notebook that I developed the night before assignment due date after realising I could have been using Tensorflow the whole time...
The model scores 7th out of 73 students.
Project 3 is about Language Model. Students are required to train a network which given the first n-1 words of a sentence, the probability distribution of the last word of the sentence. View the report in it for more details. In short, a model with TCN and LSTM with Embedding residual connection is used and achieved a score well beyond bonus.