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Tag: Dockerfile

Explain text classification model predictions using Amazon SageMaker Clarify

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance...

Add your own libraries and application dependencies to Spark and Hive on Amazon EMR Serverless with custom images

Amazon EMR Serverless allows you to run open-source big data frameworks such as Apache Spark and Apache Hive without managing clusters and servers. Many...

Best practices for Amazon SageMaker Training Managed Warm Pools

Amazon SageMaker Training Managed Warm Pools gives you the flexibility to opt in to reuse and hold on to the underlying infrastructure for a...

Gain visibility into your Amazon MSK cluster by deploying the Conduktor Platform

This is a guest post by AWS Data Hero and co-founder of Conduktor, Stephane Maarek. Deploying Apache Kafka on AWS is now easier, thanks...

A Complete Guide for Deploying ML Models in Docker

Introduction on Docker Docker is everywhere in the world of the software industry today. Docker is a DevOps tool and is very popular in the...

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