Machine Learning


Introducing Grafana Machine Learning for Grafana Cloud, with metrics forecasting

At GrafanaCONline in June, we talked about the future of machine learning at Grafana Labs. Four months later, we are excited to introduce Grafana Machine Learning for Grafana Cloud, with our metrics forecasting capability. It’s available now to all customers on Pro or Advanced plans. If you’re not already using Grafana Cloud, you can sign up for a free 14-day trial of Grafana Cloud Pro here.


Driving Data Innovation With MLTK v5.3

Many of you may have seen our State of Data Innovation report that we released recently; what better way to bring data and innovation closer together than through Machine Learning (ML)? In fact, according to this report, Artificial Intelligence (AI)/ML was the second most important tool for fueling innovation. So, naturally we have paired this report with a new release of the Machine Learning Toolkit (MLTK)!

Feature Engineering For Machine Learning: The Ultimate Guide

Almost all industries use artificial intelligence (AI) and machine learning (ML) today. As part of the so-called disruptive technologies, they've upended current technologies and have affected people in the way they work, do business, and spend their leisure time. And, with the pace these techs are advancing, they'll continue to be at the forefront of technological progress in the next few years.

Put the Machines to Work for You: A Modern Approach to Increase IT Agility

Putting machines to work to enhance our everyday lives has been well-ingrained in our society for at least a couple of centuries now. IT workers use machine learning (ML) in their daily work routines, even if they don’t consciously realize it. Automated email alerts, issue escalations, and security patching are just a few examples of how ML has put the systems we rely on to work for us.


A developer's guide to machine learning security

Machine learning has become an important component of many applications we use today. And adding machine learning capabilities to applications is becoming increasingly easy. Many ML libraries and online services don’t even require a thorough knowledge of machine learning. However, even easy-to-use machine learning systems come with their own challenges. Among them is the threat of adversarial attacks, which has become one of the important concerns of ML applications.

Improve MTTR by Using Machine Learning for Alerts

Did you know Freshservice can help reduce noise by up to 50% using ML algorithms? Watch our video to learn how Freshservice uses machine learning to translate the swarm of signals from the monitoring tools into stories you can act upon fast. Join us to explore our latest ITOM features to break the silos in your processes. #letsTalkITOM

Building a Real-Time ML Pipeline with a Feature Store - MLOps Live #16

With the growing business demand for real-time use cases such as NLP, fraud prediction, predictive maintenance and real-time recommendations, ML teams are feeling immense pressure to solve the operational challenges of real-time feature engineering for machine learning, in a simple and reproducible way. This is where online feature stores come in. An online feature store accelerates the development and deployment of online AI applications by automating feature engineering and providing a single pane of glass to build, share and manage features across the organization.

Using Automated Model Management for CPG Trade Success

CPG executives invest billions of dollars in trade and consumer promotion investments every year, spending as much as 15-20% of their total annual revenues on these initiatives. However, studies show that less than 72% of these promotions don’t break even and 59% of them fail. Despite these troubling statistics, most CPG organizations continue to design and execute essentially the same promotions year after year with negligible hope of obtaining sustained ROI.


Go with your Data Flow - Improve your Machine Learning Pipelines

Many of you are familiar with Splunk’s Machine Learning Toolkit (MLTK) and the Deep Learning Toolkit (DLTK) for Splunk and have started working with either one to address security, operations, DevOps or business use cases. A frequently asked question that I often hear about MLTK is how to organize the data flow in Splunk Enterprise or Splunk Cloud.