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?
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?
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?
2020 will be about simplifying the way from data science to production, with an emphasis on bringing real – and scalable – business value.
A step by step tutorial covering experiment tracking complexity concerns and how to solve them with MLRun, a new open source framework which optimizes the management of machine learning operations.
The notions of collaborative innovation, openness and portability are driving enterprises to embrace open source technologies. Anyone can download and install Kubernetes, Jupyter, Spark, TensorFlow and Pytorch to run machine learning applications, but making these applications enterprise grade is a whole different story.
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.