In this tutorial, we use a Nuclio serverless function to “listen” to a Kafka stream and then ingest its events into our time series table.
In this tutorial, we use a Nuclio serverless function to “listen” to a Kafka stream and then ingest its events into our time series table.
Still waiting for ML training to be over? Tired of running experiments manually? Not sure how to reproduce results? Wasting too much of your time on devops and data wrangling?
It's a wrap! We had a full house at MLOps NYC, Iguazio's annual conference about managing and automating machine learning pipelines in order to bring data science into business applications. With an outstanding caliber of speakers and audience, the MLOps conference went beyond theory, shedding light on painful and successful machine learning experiences which involve...
Let’s explore the complexity and vulnerability of IT infrastructure and how to build a modern IT infrastructure monitoring solution, using a combination of time series databases with machine learning.
Today we all choose between the simplicity of Python tools (pandas, Scikit-learn), the scalability of Spark and Hadoop, and the operation readiness of Kubernetes. We end up using them all.
You’ve played around with machine learning, learned about the mysteries of neural networks, almost won a Kaggle competition and now you feel ready to bring all this to real world impact. It’s time to build some real AI-based applications.