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Top 8 Machine Learning Algorithms

Data Science Dojo

By understanding machine learning algorithms, you can appreciate the power of this technology and how it’s changing the world around you! Let’s unravel the technicalities behind this technique: The Core Function: Regression algorithms learn from labeled data , similar to classification.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. But what is an anomaly and why is detecting it important?

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Semantic image search for articles using Amazon Rekognition, Amazon SageMaker foundation models, and Amazon OpenSearch Service

AWS Machine Learning Blog

This solution uses our event-driven services Amazon EventBridge , AWS Step Functions , and AWS Lambda to orchestrate the process of extracting metadata from the images using Amazon Rekognition. Using the k-nearest neighbors (k-NN) algorithm, you define how many images to return in your results.

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8 of the Top Python Libraries You Should be Using in 2024

ODSC - Open Data Science

Scikit-learn A machine learning powerhouse, Scikit-learn provides a vast collection of algorithms and tools, making it a go-to library for many data scientists. Interested in attending an ODSC event? Learn more about our upcoming events here. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

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Everything to know about Anomaly Detection in Machine Learning

Pickl AI

Observations that deviate from the majority of the data are known as anomalies and might take the shape of occurrences, trends, or events that differ from customary or expected behaviour. Finding anomalous occurrences that might point to intriguing or potentially significant events is the aim of anomaly detection.

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Coactive AI’s CEO: quality beats quantity for data selection

Snorkel AI

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process? AB : Got it. Thank you.

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Coactive AI’s CEO: quality beats quantity for data selection

Snorkel AI

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process? AB : Got it. Thank you.