Hands-On Artificial Intelligence on Amazon Web Services: Decrease the time to market for AI and ML applications with the power of AWS

Hands-On Artificial Intelligence on Amazon Web Services: Decrease the time to market for AI and ML applications with the power of AWS
Hands-On Artificial Intelligence on Amazon Web Services: Decrease the time to market for AI and ML applications with the power of AWS by Subhashini Tripuraneni
English | 2019 | ISBN: 1789534146 | 426 Pages | EPUB | 992 MB

Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly
From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS.
With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS.
The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning.
By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle.
What you will learn

  • Gain useful insights into different machine and deep learning models
  • Build and deploy robust deep learning systems to production
  • Train machine and deep learning models with diverse infrastructure specifications
  • Scale AI apps without dealing with the complexity of managing the underlying infrastructure
  • Monitor and Manage AI experiments efficiently
  • Create AI apps using AWS pre-trained AI services