Week 1: Sentiment Analysis with Logistic Regression
Learn how to extract features from text into numerical vectors, then build a binary classifier for tweets using logistic regression.
Week 2: Sentiment Analysis with Naïve Bayes
Understand the theory behind Bayes’ rule for conditional probabilities, then apply it toward building a Naive Bayes tweet classifier of your own.
Week 3: Vector Space Models
Vector space models capture semantic meaning and relationships between words. You’ll learn how to create word vectors that capture dependencies between words, then visualize their relationships in two dimensions using PCA.
Week 4: Machine Translation and Document Search
Learn how to transform word vectors and assign them to subsets using locality-sensitive hashing to perform machine translation and document search.