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Machine Learning

Combining supervised and unsupervised machine learning for DGA detection

It is with great excitement that we announce our first-ever supervised ML and security integration! Today, we are releasing a supervised ML solution package to detect domain generation algorithm (DGA) activity in your network data. In addition to a fully trained detection model, our release contains ingest pipeline configurations, anomaly detection jobs, and detection rules that will make your journey from setup to DGA detection smooth and easy.

Top 10 AI & Data Podcasts You Should Be Listening To

With the speed of change in artificial intelligence (AI) and big data, podcasts are an excellent way to stay up-to-date on recent developments, new innovations, and gain exposure to experts’ personal opinions, regardless if they can be proven scientifically. Great examples of the thought-provoking topics that are perfect for a podcast’s longer-form, conversational format include the road to AGI, AI ethics and safety, and the technology’s overall impact on society.

Artificial Intelligence vs Machine Learning in Technology

‍As children we believed in magic, imagined, and a fantasy where robots would one day follow our commands, undertaking our most meager tasks and even help with our homework at the push of a button! But sadly it always seemed that these beliefs, along with the idea of self-driven aero cars and jetpacks, belonged in a future beyond our imagination or in a Hollywood Sci-fi. Would we ever get to experience the future in our lifetime?

Predictions: The AI Challenges of 2021

The overall theme of Splunk’s four-part 2021 Predictions report is the rapid acceleration of digital transformation, driven by the specific event of the COVID-19 pandemic, and the momentum of data technologies that have brought us into a true Data Age. Nowhere is that acceleration going to be more transformative than around the application of artificial intelligence and machine learning.

Ronald van Loon & Sendur Sellakumar | Splunk Cloud Is Rebuilt for the Data Age

Data analyst Ronald van Loon sits down with Splunk’s Sendur Sellakumar to discuss how companies can succeed in the data age. The conversation covers shifting to a cloud-native experience, honing in on a data-to-everything strategy, and customer-centric approach to data and product development. The majority of organizations are not prepared for an influx of data on the scale promised by the dawning data age. To thrive, every organization needs a complete view of its data — real-time insights with the ability to take real-time action.

Finding the Bug in the Haystack with Machine Learning: Logz.io Exceptions in Kibana

Logz.io is releasing its AI-powered Exceptions, a revamped version of our Application Insights, fully embedded in your Kibana Discover experience, to boost your troubleshooting experience and help you find bugs in the log haystack.

Splunk with the Power of Deep Learning Analytics and GPU Acceleration

Splunk is a machine data platform with advanced analytic capabilities that allows anyone to get valuable insights from their data. With unlimited use cases, you can leverage SPL to run any analytics you want. SPL has been supporting native machine learning capabilities for some time now. All you have to do is install the Splunk Machine Learning Toolkit (MLTK) and you are good to start predicting !

Deploying Kubeflow everywhere: desktop, edge, and IoT devices

Kubeflow, the ML toolkit on K8s, now fits on your desktop and edge devices! 🚀 Kubeflow provides the cloud-native interface between Kubernetes and data science tools: libraries, frameworks, pipelines, and notebooks. > Read more about what is Kubeflow To make Kubeflow the standard cloud-native tool for MLOps within the AI landscape, the open-source community has accomplished the aggregation and integration of many projects on top of Kubernetes.