A step by step tutorial on working with Spark in a Kubernetes environment to modernize your data science ecosystem
Discover Iguazio’s “cloud-like” Intelligent Edge, powered by NVIDIA EGX, which enables data and compute intensive processing with seamless usability.
Modernize your IT Infrastructure Monitoring by Combining Time Series Databases with Machine Learning
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.
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.
Ever wonder if it’s possible to train machine learning (ML) models with regulated data which can’t be sent to the cloud? Has your edge solution gathered so much data that it just doesn’t make sense to send it all to
Here’s the problem: we are always under pressure to reduce the time it takes to develop a new model, while datasets only grow in size. Running a training job on a single node is pretty easy, but nobody wants to wait hours and then run it again, only to realize that it wasn’t right to begin with.
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?