Book Image

The Applied AI and Natural Language Processing Workshop

By : Krishna Sankar, Jeffrey Jackovich, Ruze Richards
Book Image

The Applied AI and Natural Language Processing Workshop

By: Krishna Sankar, Jeffrey Jackovich, Ruze Richards

Overview of this book

Are you fascinated with applications like Alexa and Siri and how they accurately process information within seconds before returning accurate results? Are you looking for a practical guide that will teach you how to build intelligent applications that can revolutionize the world of artificial intelligence? The Applied AI and NLP Workshop will take you on a practical journey where you will learn how to build artificial intelligence (AI) and natural language processing (NLP) applications with Amazon Web services (AWS). Starting with an introduction to AI and machine learning, this book will explain how Amazon S3, or Amazon Simple Storage Service, works. You’ll then integrate AI with AWS to build serverless services and use Amazon’s NLP service Comprehend to perform text analysis on a document. As you advance, the book will help you get to grips with topic modeling to extract and analyze common themes on a set of documents with unknown topics. You’ll also work with Amazon Lex to create and customize a chatbot for task automation and use Amazon Rekognition for detecting objects, scenes, and text in images. By the end of The Applied AI and NLP Workshop, you’ll be equipped with the knowledge and skills needed to build scalable intelligent applications with AWS.
Table of Contents (8 chapters)
Preface

Core S3 Concepts

The S3 hierarchy includes the following concepts:

  • Type of data storage: S3 is a key-value store. You provide a unique key, and AWS stores your data as a value. You retrieve the data using the key.
  • Keys: The key is the name assigned to an object that uniquely identifies it inside a bucket. All objects in a bucket have one key associated with them.
  • Objects: Objects are what you store. They are not updatable: if you need to change one byte in the value, you will have to upload the entire object again.
    Figure 1.3: Object storage using a unique key and myBucket

Figure 1.3: Object storage using a unique key and myBucket

  • Bucket: Just like a folder, a bucket is a container where you store objects. Buckets are created at the root level and do not have a filesystem hierarchy. More specifically, you can have multiple buckets, but you cannot have sub-buckets within a bucket. Buckets are the containers for objects, and you can control (create, delete, and list objects in the bucket) access, view access logs, and select the geographical region where Amazon S3 will store the bucket.
  • Region: Region refers to the geographical region, such as us-central or ap-south, where S3 stores a bucket, based on the user's preference. The region can be selected when creating a bucket. The location should be based on where the data will be accessed the most. Overall, specific region selection has the biggest impact if S3 is used to store files for a website that's exclusively accessed in a specific geographic region.

    The object storage in a bucket with different forms is as follows:

    Figure 1.4: Object storage

Figure 1.4: Object storage

S3 Operations

The S3 API is quite simple, and it includes the following operations for the entity in question:

  • Bucket: Create, delete, and list keys in a bucket
  • Object: Write, read, and delete

Here's an example:

Figure 1.5: Object stored in myBucket

Figure 1.5: Object stored in myBucket