Building Chatbots with Python: Using Natural Language Processing and Machine Learning

This book teaches you how to build, train, and deploy your own chatbot using open source tools and Python. It covers natural language processing, API.ai platform, and key points of integration and deployment.

Format: Paperback / softback
Length: 192 pages
Publication date: 13 December 2018
Publisher: APress

Building Your Own Chatbot Using Python and Open Source Tools: A Comprehensive Guide
Introduction:
Chatbots have become an increasingly popular technology in recent years, with their ability to provide personalized and efficient customer service. In this book, we will explore the architecture of chatbots, natural language processing (NLP) techniques, and how to build a custom language processing platform using the Natural Language Toolkit (NLTK). We will also learn how to integrate chatbots with various platforms such as Facebook, Slack, and Telegram, and deploy them on our own server with AWS.
Chapter 1: Introduction to Chatbots:
In this chapter, we will provide a brief overview of chatbots and their architecture. We will discuss the different components of a chatbot, such as the user interface, the natural language processing engine, and the database. We will also explore the different types of chatbots, such as rule-based chatbots, machine learning chatbots, and hybrid chatbots.
Chapter 2: Natural Language Processing with NLTK:
In this chapter, we will dive into natural language processing with the Natural Language Toolkit (NLTK). We will learn about the different NLP techniques, such as tokenization, stemming, lemmatization, and part-of-speech tagging. We will also learn how to use NLTK to build a custom language processing platform for our chatbot.
Chapter 3: Building a Custom Language Processing Platform:
In this chapter, we will build a custom language processing platform for our chatbot using the Natural Language Toolkit (NLTK). We will start by creating a simple chatbot that can understand and respond to basic user queries. We will then add more advanced features such as sentiment analysis, entity extraction, and context awareness.
Chapter 4: Integrating Chatbots with Various Platforms:
In this chapter, we will learn how to integrate chatbots with various platforms such as Facebook, Slack, and Telegram. We will discuss the different APIs and protocols used by these platforms and how to implement them in our chatbot. We will also learn how to handle user authentication and authorization.
Chapter 5: Deploying Chatbots on Your Own Server with AWS:
In this chapter, we will learn how to deploy chatbots on our own server with AWS. We will discuss the different AWS services that can be used for hosting chatbots, such as Amazon EC2, Amazon S3, and Amazon Lambda. We will also learn how to configure and deploy our chatbot on AWS.
Conclusion:
Building your own chatbot using Python and open source tools can be a challenging but rewarding experience. By following the steps outlined in this book, you will gain the skills and knowledge necessary to build a custom language processing platform for your chatbot, integrate it with various platforms, and deploy it on your own server with AWS. Whether you are an intermediate Python developer or a beginner, this book will provide you with the tools and knowledge you need to succeed in the world of chatbots.

Weight: 434g
Dimension: 179 x 254 x 13 (mm)
ISBN-13: 9781484240953
Edition number: 1st ed.