Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (pdf)

$12.00

Author Chris Fregly, Antje Barth
Edition 1
Edition Year 2021
Format PDF
ISBN 9781492079392
Language English
Number Of Pages 688
Publisher O’Reilly Media

Description

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 moreWith 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 upyour skills.

Additional information

Author

Chris Fregly, Antje Barth

Edition

1

Edition Year

2021

Format

PDF

ISBN

9781492079392

Language

English

Number Of Pages

688

Publisher

O'Reilly Media

Reviews

There are no reviews yet.

Be the first to review “Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (pdf)”

Your email address will not be published. Required fields are marked *