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

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

作者
Subhashini Tripuraneni、Charles Song
语言
英语
出版社
Packt Publishing 版次:1
出版日期
2019年10月4日
纸书页数
426页
电子书格式
epub,pdf,mobi,azw3,txt,fb2,djvu
文件大小
22550 KB
下载次数
7134
更新日期
2023-05-20
运行环境
PC/Windows/Linux/Mac/IOS/iPhone/iPad/iBooks/Kindle/Android/安卓/平板
内容简介

Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly

Key Features

Explore popular machine learning and deep learning services with their underlying algorithms

Discover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services

Design robust architectures to enable experimentation, extensibility, and maintainability of AI apps

Book Description

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

Who this book is for

This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected. Table of Contents

Introduction to Artificial Intelligence on AWS

Anatomy of an Modern AI Application

Detecting and Translating Text with AWS Rekognition and AWS Translate

Performing speech-to-text and Vice-versa with AWS Transcribe and AWS Polly

Extracting Information from Text with AWS Comprehend

Building a Voice Chatbot with AWS Lex

Working with Amazon SageMaker

Creating Machine Learning Inference Pipelines with Amazon SageMaker

Discovering Topics in Text Collections using Amazon SageMaker

Classifying Images using Amazon SageMaker

Sales Forecasting with Deep Learning and Auto Regression

Model Accuracy Degradation and Feedback Loop

What’s Next

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