Educative - Mastering Natural Language Processing

Natural language processing (NLP) enables computers to understand, interpret, and generate human language meaningfully, contextually, and relevantly. NLP applications, including virtual assistants like Siri and Alexa, language translation services, and more, are widespread. The field continues to evolve with ongoing research and technological advancements, making it a highly valued skill amongst machine learning engineers in the tech industry. The Skill Path begins with a comprehensive introduction to the fundamental concepts of natural language processing (NLP) and machine learning. Next, you’ll extensively cover spaCy’s (a widely used Python library for machine learning) architecture and gain hands-on experience using spaCy for real-world NLP applications. Finally, you’ll use these skills to build some applications using NLP.

Learning Objectives

• A familiarity with natural language processing and machine learning
• A working knowledge of text classification methodologies
• An understanding of different techniques for interpreting complex deep learning models applied to NLP
• The ability to process raw text into usable data to apply machine learning techniques

Path Content

Module 1 - Natural Language Processing with Machine Learning

Get familiar with the basic machine learning techniques used in natural language processing.

Module 2 - Mastering spaCy

Learn about tokenization, entity recognition, and syntactic parsing using spaCy to apply NLP techniques.

Module 3 - Building Advanced Deep Learning and NLP Projects

Get hands-on experience in NLP with challenging applications.