Coursera Natural Language Processing Specialization

This repository contains material related to Coursera Natural Language Processing Specialization. Consisting of a number of Jupyter Notebooks subgrouped into directories Assignment and Class-Notes

Content

Natural Language Processing with Classification and Vector Spaces

Sentiment Analysis with Logistic Regression: Learn to extract features from text into numerical vectors, then build a binary classifier for tweets using logistic regression.

• Assignment
• Class-Notes

Sentiment Analysis with Naïve Bayes: Learn the theory behind Bayes' rule for conditional probabilities, then apply it toward building a Naive Bayes tweet classifier.

Vector Space Models: Vector space models capture semantic meaning and relationships between words. Learn how to create word vectors that capture dependencies between words, then visualize their relationships in two dimensions using PCA.

Machine Translation and Document Search: Learn to transform word vectors and assign them to subsets using locality sensitive hashing, in order to perform machine translation and document search.