Natural Language Processing

Introduction

Welcome to the labs.earth collaborative laboratory tutorials on machine learning.

The natural language processing (NLP) tutorials will start with the basics and progress to advanced real world applications.

The tutorials go beyond explaining the code and steps, to include the answers to the anticipated what and why questions.

Before the advent of machine learning with computer vision and today's modern ML/CV frameworks, working with and building real world applications was once the exclusive domain of imaging scientists. The Gap framework extends modern natural language processing to software developers, whom are familar with object oriented programming (OOP), object relational models (ORM), design patterns (e.g., MVC), asynchronous programming (AJAX), and microservice architectures.

For the data analyst and statisticians whom feel they don't have the necessary software development background, we encourage you to visit the collaborative lab's training site for fundamentials in modern software programming. Likewise, for those software developers whom feel they don't have the necessary background in statistics and machine learning, we encourage you to visit the collaborative lab's training site for fundamentials in modern statistics and machine learning.

As far as our team and contributers, they keep a single phrase in mind when designing, coding and building tutorials. They like to say that Gap is:

                                        Machine Learning for Humans

The First Steps in using Gap for Natural Language Processing (NLP)