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Pluralsight

Implement Natural Language Processing for Word Embedding

via Pluralsight

Overview

This course will teach you how to use word embeddings to use deep learning for NLP.

Natural language processing (NLP) is a set of tools and techniques that enables us to unlock the power of analyzing text. In this course, Implement Natural Language Processing for Word Embedding, you’ll learn how to use word embeddings to use neural networks for NLP. First, you’ll explore what word embeddings are and the most basic embedding: one hot encoding. Next, you’ll discover how to use word embeddings to do sentiment analysis. Finally, you’ll learn how to fine-tune existing word embeddings to improve your models as well as debase our embeddings for fairness. When you’re finished with this course, you’ll have the skills and knowledge of natural language processing needed to leverage word embeddings to create amazing NLP solutions with deep learning.

Syllabus

  • Course Overview 1min
  • Why Process Text? 10mins
  • Training Word Representations 51mins
  • Fine-tuning Word Representations 30mins

Taught by

Axel Sirota

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