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Implement Natural Language Processing for Word Embedding

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

Axel Sirota - Pluralsight course - Implement Natural Language Processing for Word Embedding
by Axel Sirota

What you'll learn

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.

Table of contents

About the author

Axel Sirota - Pluralsight course - Implement Natural Language Processing for Word Embedding
Axel Sirota

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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