### Course 1: Natural Language Processing with Classification and Vector Spaces

In Course 1 of the Natural Language Processing Specialization, you will:

a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes,

b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and

c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality-sensitive hashing to relate words via approximate k-nearest neighbor search.

**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.