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Machine Learning

Here's how Machine Learning puts the 'personal' in ecommerce personalization

You can transform your search box into your sales rep—when you have the right tools. An impactful customer experience that drives purchases and loyalty isn't just about delivering what a customer says they want — it's about predicting and proactively serving up what they need. We might be able to imagine this work in a store with salespeople. But as organizations scale and customer interactions happen across digital and in-person mediums, their data grows.

Monitoring Ubuntu 20.04 and Activating ML with Netdata

Sometimes a hat is just a hat, the truth is just the truth, and the clearly most popular example of a category is plain to see. In this case, Ubuntu is the most popular Linux distribution currently available. With the operating system’s superior popularity also comes an amazing amount of community support.

Test Driving Machine Learning (ML) Anomaly Advisor

Netdata’s new Anomaly Advisor feature lets you quickly identify potentially anomalous metrics during a particular timeline of interest. This results in considerably speeding up your troubleshooting workflow and saving valuable time when faced with an outage or issue you are trying to root cause.

How to configure Netdata's all-new Anomaly Advisor, powered by ML, for real-time troubleshooting

Netdata's Lead Machine Learning Engineer, Andrew Maguire, walks through how to configure the all-new Anomaly Advisor. This new feature lets you troubleshoot in real-time, at scale, by identifying periods of time with raised anomaly rates across your entire infrastructure. In this guided video, Andrew will explain how to enable Netdata's ML functionality then, how to set up unsupervised anomaly detection with minimal configuration, and lastly how the Anomaly Advisor works to speed up troubleshooting when an incident occurs.

Introducing Anomaly Advisor for troubleshooting at scale

Troubleshoot at scale with our all-new, lightweight Anomaly Advisor, powered by machine learning. The Anomaly Advisor finds periods of time with elevated anomaly rates across your entire infrastructure faster than ever before. This new feature works along with our ML unsupervised models on the edge, making your troubleshooting trouble-free! Even better, the Anomaly Advisor requires minimal configuration and is extremely lightweight. No need to worry about exhausting your CPU usage.

Researchers test the power of machine learning to unravel long Covid's mysteries

Long Covid, with its constellation of symptoms, is proving a challenging moving target for researchers trying to conduct large studies of the syndrome. As they take aim, they’re debating how to responsibly use growing piles of real-world data — drawing from the full experiences of long Covid patients, not just their participation in stewarded clinical trials.

Monitor model performance with Superwise's offering in the Datadog Marketplace

Superwise is a monitoring platform that provides model observability for high-scale machine learning (ML) operations. Superwise provides teams with out-of-the-box (OOTB) metrics on their models’ production behavior, so they can effectively address drift, data quality issues, and other problems before they negatively impact business.

Machine learning tool to speed up treatment of traumatic brain injury

A team of data scientists from the University of Pittsburgh School of Medicine in the US, and neurotrauma surgeons from the University of Pittsburgh Medical Centre, has developed the first automated brain scans and machine-learning techniques to inform outcomes for patients who have severe traumatic brain injuries. The advanced machine-learning algorithm can analyse vast volumes of data from brain scans and relevant clinical data from patients.

CNCF Live: Power up your machine learning - Automated anomaly detection

Our Analytics & ML lead Andrew Maguire recently had a chance to share our new Anomaly Advisor feature with the wider CNCF community. In his demonstration he did some light chaos engineering (using Gremlin and stress-ng) to generate some real anomalies on his infrastructure and watch how it all played out in the Anomaly Advisor in Netdata Cloud. There were also some great questions and discussion from the audience around ML in general and in the observability space itself.

Machine learning model can distinguish antibody targets

A new study shows that it is possible to use the genetic sequences of a person’s antibodies to predict what pathogens those antibodies will target. Reported in the journal Immunity, the new approach successfully differentiates between antibodies against influenza and those attacking SARS-CoV-2, the virus that causes COVID-19.