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Classification vs. Clustering- Which One is Right for Your Data?

Analytics Vidhya

Definitely not. This is where the organization part comes in— by categorizing the brands as a whole or taking a more […] The post Classification vs. Clustering- Which One is Right for Your Data? Introduction Imagine walking into a shopping mall with hundreds of brands and products, all jumbled up and randomly placed in the shops.

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Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool for landmine contamination to identify hazardous clusters under geographic and budget constraints, experimentally reducing false alarms and clearance time by half. The major components of RELand are illustrated in Fig.

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Improve Cluster Balance with CPD Scheduler?—?Part 2

IBM Data Science in Practice

Improve Cluster Balance with CPD Scheduler — Part 2 The default Kubernetes scheduler has some limitations that cause unbalanced clusters. In an unbalanced cluster, some of the worker nodes are overloaded and others are under-utilized. we will use “cluster balance” and “resource usage balance” interchangeably.

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Start using Liquid Clustering instead of Partitioning for Delta tables in Databricks

Towards AI

Revolutionizing the way we organize the data, Databricks introduced a game-changer called Liquid Clustering in this year’s Data + AI Summit. An innovative feature that redefines the boundaries of partitioning and clustering for Delta tables. Writing data to a clustered table — Most operations do not automatically cluster data on write.

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How Aetion is using generative AI and Amazon Bedrock to unlock hidden insights about patient populations

AWS Machine Learning Blog

Smart Subgroups For a user-specified patient population, the Smart Subgroups feature identifies clusters of patients with similar characteristics (for example, similar prevalence profiles of diagnoses, procedures, and therapies). The AML feature store standardizes variable definitions using scientifically validated algorithms.

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Data Analytics Tutorial: Mastering Types of Statistical Sampling

Pickl AI

Simple Random Sampling Definition and Overview Simple random sampling is a technique in which each member of the population has an equal chance of being selected to form the sample. Select clusters randomly from the population. Include all members within the chosen clusters in the sample. Analyze the obtained sample data.

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Deploy Amazon SageMaker pipelines using AWS Controllers for Kubernetes

AWS Machine Learning Blog

ACK allows you to take advantage of managed model building pipelines without needing to define resources outside of the Kubernetes cluster. This configuration takes the form of a Directed Acyclic Graph (DAG) represented as a JSON pipeline definition. kubectl for working with Kubernetes clusters. yq for YAML processing.

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