Data Science on AWS

· "O'Reilly Media, Inc."
Libro electrónico
524
Páginas
Apto
Las calificaciones y opiniones no están verificadas. Más información

Acerca de este libro electrónico

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.
  • Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more
  • Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot
  • Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment
  • Tie everything together into a repeatable machine learning operations pipeline
  • Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka
  • Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

Acerca del autor

Chris Fregly is a Developer Advocate for AI and Machine Learning at AWS, based in San Francisco, California. He is also the founder of the Advanced Spark, TensorFlow, and KubeFlow Meetup Series based in San Francisco. Chris regularly speaks at AI and Machine Learning conferences across the world including the O’Reilly AI, Strata, and Velocity Conferences. Previously, Chris was Founder at PipelineAI where he worked with many AI-first startups and enterprises to continuously deploy ML/AI Pipelines using Apache Spark ML, Kubernetes, TensorFlow, Kubeflow, Amazon EKS, and Amazon SageMaker. He is also the author of the O’Reilly Online Training Series “High Performance TensorFlow in Production with GPUs”

Antje Barth is a Developer Advocate for AI and Machine Learning at AWS, based in Düsseldorf, Germany. She is also co-founder of the Düsseldorf chapter of Women in Big Data Meetup. Antje frequently speaks at AI and Machine Learning conferences and meetups around the world, including the O’Reilly AI and Strata conferences. Besides ML/AI, Antje is passionate about helping developers leverage Big Data, container and Kubernetes platforms in the context of AI and Machine Learning. Prior to joining AWS, Antje worked in technical evangelist and solutions engineering roles at MapR and Cisco.

Califica este libro electrónico

Cuéntanos lo que piensas.

Información de lectura

Smartphones y tablets
Instala la app de Google Play Libros para Android y iPad/iPhone. Como se sincroniza de manera automática con tu cuenta, te permite leer en línea o sin conexión en cualquier lugar.
Laptops y computadoras
Para escuchar audiolibros adquiridos en Google Play, usa el navegador web de tu computadora.
Lectores electrónicos y otros dispositivos
Para leer en dispositivos de tinta electrónica, como los lectores de libros electrónicos Kobo, deberás descargar un archivo y transferirlo a tu dispositivo. Sigue las instrucciones detalladas que aparecen en el Centro de ayuda para transferir los archivos a lectores de libros electrónicos compatibles.