Using GPUaaS in this way simplifies and automates data science, boosting productivity and significantly reducing time to market.
Here's what business leaders can do to reduce the costs of their AI projects and see positive business results sooner.
Using GPUaaS in this way simplifies and automates data science, boosting productivity and significantly reducing time to market.
Summary of my MLOps NYC talk, major AI/ML & Data challenges and how they will be solved with emerging open source technologies
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.