Cargando…

Intelligent Document Processing with AWS AI/ML A Comprehensive Guide to Building IDP Pipelines with Applications Across Industries /

Build real-world artificial intelligence applications across industries with the help of intelligent document processing Key Features Tackle common document processing problems to extract value from any type of document Unlock deeper levels of insights on IDP in a more structured and accelerated way...

Descripción completa

Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autor principal:	Sahu, Sonali
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Birmingham : Packt Publishing, Limited, 2022.
Temas:	Amazon Web Services (Firm) Machine learning. Artificial intelligence > Computer programs.
Acceso en línea:	Texto completo (Requiere registro previo con correo institucional)

Ejemplares similares

Beginning machine learning with AWS /
por: Jackovich, Jeffrey, et al.
Publicado: (2019)

MACHINE LEARNING ENGINEERING ON AWS building, scaling, and securing machine learning systems and MLOps pipelines in production /
por: Lat, Joshua Arvin
Publicado: (2022)

MACHINE LEARNING ENGINEERING ON AWS building, scaling, and securing machine learning systems and MLOps pipelines in production /
por: Lat, Joshua Arvin
Publicado: (2022)

Data Science mit AWS : end-to-end pipelines für continuous machine learning implementieren /
por: Fregly, Chris, et al.
Publicado: (2022)

MLOps for containers with AWS and GCP /
Publicado: (2021)

Hands-on artificial intelligence on Amazon Web Services : decrease the time to market for AI and ML applications with the power of AWS /
por: Tripuraneni, Subhashini, et al.
Publicado: (2019)

Hands-on artificial intelligence on Amazon Web Services : decrease the time to market for AI and ML applications with the power of AWS /
por: Tripuraneni, Subhashini, et al.
Publicado: (2019)

52 Weeks of AWS : AWS ML certification,
Publicado: (2022)

AI as a Service
por: Elger, Peter
Publicado: (2020)

MLOps talks I want to attend at re:Invent 2021 : /
Publicado: (2021)

Deploying Spark ML pipelines in production on AWS : how to publish pipeline artifacts and run pipelines in production /
Publicado: (2017)

Making reinforcement learning practical for real-world developers /
Publicado: (2019)

Natural Language Processing with AWS AI Services
por: M, Mona, et al.
Publicado: (2021)

Amazon SageMaker Best Practices Proven Tips and Tricks to Build Successful Machine Learning Solutions on Amazon SageMaker.
por: Muppala, Sireesha
Publicado: (2021)

Hands-on artificial intelligence on Amazon Web Services : decrease the time to market for AI and ML applications with the power of AWS /
por: Tripuraneni, Subhashini, et al.
Publicado: (2019)

Using AWS Sagemaker.
Publicado: (2021)

Machine Learning in the AWS Cloud Add Intelligence to Applications with AWS SageMaker and AWS Rekognition.
por: Mishra, Abhishek
Publicado: (2019)

52 weeks of AWS,
Publicado: (2022)

Machine learning with AWS : explore the power of cloud services for your machine learning and artificial intelligence projects /
por: Jackovich, Jeffrey
Publicado: (2018)

Machine learning fundamentals with Amazon SageMaker on AWS : LiveLessons /
Publicado: (2020)

Introduction to Amazon machine learning : learn how to build data driven predictive applications with Amazon Web Services (AWS) /
Publicado: (2017)

No-code machine learning using Amazon AWS SageMaker Canvas.
Publicado: (2022)

Pretrain Vision and Large Language Models in Python End-To-end Techniques for Building and Deploying Foundation Models on AWS /
por: Webber, Emily
Publicado: (2023)

Learn how to build intelligent data applications with Amazon Web Services (AWS) : understanding and using AWS products and services, AWS Data Pipeline, Kinesis Analytics, RDS and Redshift databases, and Amazon Machine Learning /
Publicado: (2017)

Amazon machine learning /
Publicado: (2019)

SageMaker Studio Lab first thoughts : Amazon SageMaker Studio Lab /
Publicado: (2021)

End-to-end machine learning : from training a model to deploying to the cloud.
Publicado: (2022)

Getting started with Amazon SageMaker Studio : learn to build end-to-end machine learning projects in the SageMaker machine learning IDE /
por: Hsieh, Michael
Publicado: (2022)

Automated machine learning on AWS : fast-track the development of your production-ready machine learning applications the AWS way /
por: Potgieter, Trenton, et al.
Publicado: (2022)

Serverless machine learning with Amazon Redshift ML : create, train, and deploy machine learning models using familiar SQL commands /
por: Panda, Debu, et al.
Publicado: (2023)

Practical machine learning with AWS : process, build, deploy, and productionize your models using AWS /
por: Singh, Himanshu
Publicado: (2021)

Practical machine learning with AWS : process, build, deploy, and productionize your models using AWS /
por: Singh, Himanshu
Publicado: (2021)

Learn Amazon SageMaker - Second Edition /
por: Simon, Julien
Publicado: (2021)

APPLIED MACHINE LEARNING FOR HEALTHCARE AND LIFE SCIENCES USING AWS transformational AI implementations for biotech, clinical, and healtcare organizations /
por: Ratan, Ujjwal
Publicado: (2022)

APPLIED MACHINE LEARNING FOR HEALTHCARE AND LIFE SCIENCES USING AWS transformational AI implementations for biotech, clinical, and healtcare organizations /
por: Ratan, Ujjwal
Publicado: (2022)

Intelligent Workloads at the Edge : Deliver Cyber-Physical Outcomes with Data and Machine Learning Using AWS IoT Greengrass.
por: Mitra, Indraneel
Publicado: (2022)

Assimilate Hugging Face.
Publicado: (2022)

Applied Hugging Face.
Publicado: (2022)

AWS in action : video edition /
por: Wittig, Michael, 1987-, et al.
Publicado: (2015)

Chatbots development with Amazon Lex.
Publicado: (2023)