ML-enhanced endpoint protection can keep schools safe from cyberattacks. Here are three benefits district leaders will find when investing in this advanced technology. Long before the pandemic, K–12 cyberattacks were a serious concern. The shift to remote learning has only increased the danger.

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.

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)!

If you've ever wanted to discover more about Kaggle, the online community for machine learning students and data scientist practitioners then look no further than our expert-led guide to get an overview on all the basics you need to know about this amazing opportunity provider and competition organiser.

At ElasticON Global 2021, we shared a future view of Elastic Enterprise Search and how we’re continuing to build next-generation, machine learning-powered search experiences backed by the speed, scale, and relevance of Elasticsearch. We also highlighted the many ways we plan to keep building even more flexibility into our solutions.

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.

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.