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Command-line Tools can be 235x Faster than your Hadoop Cluster (2014)

Hacker News

Adam Drake is an advisor to scale-up tech companies. He writes about ML/AI/crypto/data, leadership, and building tech teams.

Hadoop 106
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Understanding and predicting urban heat islands at Gramener using Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020. SageMaker Processing enables the flexible scaling of compute clusters to accommodate tasks of varying sizes, from processing a single city block to managing planetary-scale workloads.

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The history of Kubernetes

IBM Journey to AI blog

Borg’s large-scale cluster management system essentially acts as a central brain for running containerized workloads across its data centers. Omega took the Borg ecosystem further, providing a flexible, scalable scheduling solution for large-scale computer clusters. Control plane nodes , which control the cluster.

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Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning Blog

You need permissions to deploy AWS CloudFormation templates, push to the Amazon Elastic Container Registry (Amazon ECR), create Amazon Identity and Access Management (AWS IAM) roles, Amazon Lambda functions, Amazon S3 buckets, Amazon Step Functions, Amazon OpenSearch cluster, and an Amazon Cognito user pool.

AWS 132
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Top 6 Kubernetes use cases

IBM Journey to AI blog

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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What is the Snowflake Data Cloud and How Much Does it Cost?

phData

If you go back to 2014, data warehouse platforms were built using legacy architectures that had drawbacks when it came to cost, scale, and flexibility. Effectively this is a way to store the source of truth and build (or rebuild) your downstream data products (including data warehouses) from it. Historically, there were big differences.

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Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuning

AWS Machine Learning Blog

Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed almost 637,000 members to the recently launched Best Egg Financial Health platform, and empowered over 180,000 cardmembers who carry the new Best Egg Credit Card in their wallet.

ML 96