Word by Word and Word by Doc.

View Syllabus

Skills You'll Learn

Machine Translation, Word Embeddings, Locality-Sensitive Hashing, Sentiment Analysis, Vector Space Models


4.6 (1,661 ratings)
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 star
Aug 16, 2020

Awesome. The lecture are very exciting and detailed, though little hard and too straight forward sometimes, but Youtube helped in Regression models. Other then that, I was very informative and fun.

Aug 1, 2020

Video lectures are short and concise. The basic ideas are well presented. Some references for the details of vector subspaces and spanning vectors would have filled out the mathematical framework.

From the lesson
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.

Taught By

  • Placeholder

    Younes Bensouda Mourri

    Course Instructor
  • Placeholder

    Łukasz Kaiser

    Course Instructor
  • Placeholder

    Eddy Shyu

    Senior Curriculum Developer

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.