The key takeaway from this chapter should be that any machine learning model can be deployed like any other piece of code. The only difference is that we have to make room for being able to load the model again from disk. To do this, first, we need to train a model and write the model code and weights to disk using joblib. Then, we need to build a predict function, which is separated from training. Finally, we expose what we have done by using Flash with Jinja2 HTML templates.
Natural Language Processing with Python Quick Start Guide
By :
Natural Language Processing with Python Quick Start Guide
By:
Overview of this book
NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.
The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications.
We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.
We conclude by deploying these models as REST APIs with Flask.
By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.
Related Content you might be interested in
Current Title:
Natural Language Processing with Python Quick Start Guide
Table of Contents (10 chapters)
Preface
Free Chapter
Getting Started with Text Classification
Tidying your Text
Leveraging Linguistics
Text Representations - Words to Numbers
Modern Methods for Classification
Deep Learning for NLP
Building your Own Chatbot
Web Deployments
Other Books You May Enjoy
Customer Reviews