Euclidean Distance

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Получаемые навыки

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

Рецензии

4.6 (оценок: 901)
  • 5 stars
    70.36%
  • 4 stars
    23.97%
  • 3 stars
    3.88%
  • 2 stars
    0.99%
  • 1 star
    0.77%
JM

Aug 02, 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.

PY

Jul 16, 2020

Very complete and in-depth for all learners who wish to know more about NLP! Loved that the course is data science newbie friendly too - they have optional labs for numpy, matrix manipulation etc

Из урока
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.

Преподаватели

  • Younes Bensouda Mourri

    Younes Bensouda Mourri

    Course Instructor
  • Łukasz Kaiser

    Łukasz Kaiser

    Course Instructor
  • Eddy Shyu

    Eddy Shyu

    Senior Curriculum Developer

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