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AI as a Service: Serverless machine learning with AWS
AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide!
Summary
Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more.
With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services!
About the book
AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications.
What's inside
- Apply cloud AI services to existing platforms
- Design and build scalable data pipelines
- Debug and troubleshoot AI services
- Start fast with serverless templates
About the reader
For software developers familiar with cloud basics.
About the author
Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning.
Table of Contents
PART 1 - FIRST STEPS
1 A tale of two technologies
2 Building a serverless image recognition system, part 1
3 Building a serverless image recognition system, part 2
PART 2 - TOOLS OF THE TRADE
4 Building and securing a web application the serverless way
5 Adding AI interfaces to a web application
6 How to be effective with AI as a Service
7 Applying AI to existing platforms
PART 3 - BRINGING IT ALL TOGETHER
8 Gathering data at scale for real-world AI
9 Extracting value from large data sets with AI
Summary
Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more.
With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services!
About the book
AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications.
What's inside
- Apply cloud AI services to existing platforms
- Design and build scalable data pipelines
- Debug and troubleshoot AI services
- Start fast with serverless templates
About the reader
For software developers familiar with cloud basics.
About the author
Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning.
Table of Contents
PART 1 - FIRST STEPS
1 A tale of two technologies
2 Building a serverless image recognition system, part 1
3 Building a serverless image recognition system, part 2
PART 2 - TOOLS OF THE TRADE
4 Building and securing a web application the serverless way
5 Adding AI interfaces to a web application
6 How to be effective with AI as a Service
7 Applying AI to existing platforms
PART 3 - BRINGING IT ALL TOGETHER
8 Gathering data at scale for real-world AI
9 Extracting value from large data sets with AI
328 pages, Paperback
Published October 6, 2020
1 person is currently reading
32 people want to read
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Displaying 1 - 2 of 2 reviews
July 22, 2022
Este libro es una excelente introducción a la arquitectura serverless, en este caso todos los ejemplos están escritos con AWS, pero logra comunicar las ideas de manera general y establecer los principios de la arquitectura.
Presenta una introducción analítica sobre el avance de la computación y el deployment de aplicaciones y por qué es conveniente la forma de crear aplicaciones que está a punto de proponernos. Casi todos los demás capítulos son ejemplos de cómo llevar a cabo estas arquitecturas, con ejemplos concretos de código usando el Serverless Framework y tocando todas las partes del ciclo de vida de la aplicación: el desarrollo, las pruebas, la puesta en marcha, el monitoreo y observación y finalmente la parada de la aplicación.
Considero el contenido en general como una forma de crear aplicaciones sin servidor basadas completamente en servicios de nube, con aplicaciones hacia el uso de servicios de inteligencia artificial, como reconocimiento de imágenes, procesamiento de texto, generación de voz y empatado de patrones. Por esto mismo, da algunos ejemplos y detalles de las características de estos servicios, por lo que es una muy buena opción si quieres aprender más del uso y creación de programas habilitados por servicios de inteligencia artificial.
Creo además que el camino que propone es algo muy conveniente: aprovecharse de las ventajas que la computación en la nube, los servicios administrados y las últimas investigaciones en inteligencia artificial y machine learning (contra las que no podemos competir), para hacer mejores aplicaciones de manera más sencilla y que entreguen más con menos desarrollo.
Presenta una introducción analítica sobre el avance de la computación y el deployment de aplicaciones y por qué es conveniente la forma de crear aplicaciones que está a punto de proponernos. Casi todos los demás capítulos son ejemplos de cómo llevar a cabo estas arquitecturas, con ejemplos concretos de código usando el Serverless Framework y tocando todas las partes del ciclo de vida de la aplicación: el desarrollo, las pruebas, la puesta en marcha, el monitoreo y observación y finalmente la parada de la aplicación.
Considero el contenido en general como una forma de crear aplicaciones sin servidor basadas completamente en servicios de nube, con aplicaciones hacia el uso de servicios de inteligencia artificial, como reconocimiento de imágenes, procesamiento de texto, generación de voz y empatado de patrones. Por esto mismo, da algunos ejemplos y detalles de las características de estos servicios, por lo que es una muy buena opción si quieres aprender más del uso y creación de programas habilitados por servicios de inteligencia artificial.
Creo además que el camino que propone es algo muy conveniente: aprovecharse de las ventajas que la computación en la nube, los servicios administrados y las últimas investigaciones en inteligencia artificial y machine learning (contra las que no podemos competir), para hacer mejores aplicaciones de manera más sencilla y que entreguen más con menos desarrollo.
February 15, 2021
The authors cover two major topics: serverless computing on AWS and fully managed AWS machine learning services, such as Lex, Transcribe, and Comprehend.
They lean heavily on the Serverless framework, which is an Infrastructure-As-Code framework. They use Serverless to provision their resources in AWS and deploy code (NodeJS code primarily, which they provide in GitHub repos.)
They provide ample diagrams to teach big-picture concepts about creating an application stack in a serverless way. They have put a lot of time into teaching and the technical concepts.
One possible complaint is that much of the instruction is done through serverless yml files, which show the different components being created. Those are not as memorable for me personally, so I find my eyes skipping past those sections too quickly for them to make an impact. A few more AWS console views might have helped reinforce some of the AI services for me. But that's simply a style preference. Overall, a very thorough and well-written book.
They lean heavily on the Serverless framework, which is an Infrastructure-As-Code framework. They use Serverless to provision their resources in AWS and deploy code (NodeJS code primarily, which they provide in GitHub repos.)
They provide ample diagrams to teach big-picture concepts about creating an application stack in a serverless way. They have put a lot of time into teaching and the technical concepts.
One possible complaint is that much of the instruction is done through serverless yml files, which show the different components being created. Those are not as memorable for me personally, so I find my eyes skipping past those sections too quickly for them to make an impact. A few more AWS console views might have helped reinforce some of the AI services for me. But that's simply a style preference. Overall, a very thorough and well-written book.
Displaying 1 - 2 of 2 reviews