Natural Language Processing

Course Overview

Natural Language Processing is the use of machine learning and data analysis to build models and reveal insights based on natural text data. This course is designed for experienced Python developers who want to learn how to apply state of the art Natural Language Processing frameworks and techniques, such as the open source frameworks SpaCy and NLTK, to any kinds of natural language text data. Students taking this course will discover the latest techniques in semantic analysis, topic modeling, text classification, and more!

Private classes on this topic are available. We can address your organization’s issues, time constraints, and save you money, too. Contact us to find out how.

Who Should Attend

Intermediate to experienced Python developers or experienced developers coming from another programming language.

Course Objectives

Learn to work with Text Files with Python
Learn how to work with PDF files in Python
Utilize Regular Expressions for pattern searching in text
Use Spacy for ultra fast tokenization
Learn about Stemming and Lemmatization
Understand Vocabulary Matching with Spacy
Use Part of Speech Tagging to automatically process raw text files
Understand Named Entity Recognition
Visualize POS and NER with Spacy
Use SciKit-Learn for Text Classification
Use Latent Dirichlet Allocation for Topic Modelling
Learn about Non-negative Matrix Factorization
Use the Word2Vec algorithm
Use NLTK for Sentiment Analysis
Use Deep Learning to build out your own chat bot

Course Outline

Handling Text with Python

Working with PDFs

Regular Expressions