NLP Fundamentals — Embedding Words(P4)

Why Learn Embeddings?

Efficiency of Embeddings

Approaches to Learning Word Embeddings

  • Given a sequence of words, predict the next word. This is also called the language modeling task.
  • Given a sequence of words before and after, predict the missing word.
  • Given a word, predict words that occur within a window, independent of the position.

Example: Learning the Continuous Bag of Words Embeddings

The Frankenstein Dataset

Vocabulary, Vectorizer, and DataLoader

The CBOWClassifier Model

The Training Routine

Model Evaluation and Prediction

Notebook for Practice

--

--

--

AI Researcher - NLP Practitioner

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Robust fast tracking using multi-level feature transformer

Best Way to Deploy Sci-kit Learn model in dot Net Application

Machine Learning: realistic expectations

Neural Networks: Orthogonal Transformers

Customer segmentation and potential customer prediction

123

Sentiment classification with Naive Bayes, Logistic regression, and ngrams: Part 4

Reflinks vs symlinks vs hard links, and how they can help machine learning projects

Automated Text Reading and Language Translation

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Duy Anh Nguyen

Duy Anh Nguyen

AI Researcher - NLP Practitioner

More from Medium

Climbing activity recognition with video data

Making Sense of Inverse Data Flow — React

NLP with Disaster Tweets

Dialogue System_Part_1