Systems | Development | Analytics | API | Testing

MLRun Functions DEMO: Python Jupyter (Open-Source Data Science Orchestration + Experiment Tracking)

Jun 23, 2020 By Iguazio In Iguazio
MLRun is a generic and convenient mechanism for #data scientists and software developers to build, run, and monitor #machinelearning (ML) tasks and pipelines on a scalable cluster while automatically tracking executed code, metadata, inputs, and outputs. On-Premise or Barebone/Metal - including Edge AI / Analytics Customers include NetApp, Quadient, Payoneer (and many more).
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iguazio

Git-based CI / CD for Machine Learning & MLOps

Jun 22, 2020 By Yaron Haviv In Iguazio

For decades, machine learning engineers have struggled to manage and automate ML pipelines in order to speed up model deployment in real business applications. Similar to how software developers leverage DevOps to increase efficiency and speed up release velocity, MLOps streamlines the ML development lifecycle by delivering automation, enabling collaboration across ML teams and improving the quality of ML models in production while addressing business requirements.

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Bringing ML Pipelines to Production - Challenges & Solutions - MLOPs Live #1 - With S&P Global

May 31, 2020 By Iguazio In Iguazio
The session — featuring Ganesh Nagarathnam, Director Analytics & ML Engineering at S & P Global Market Intelligence, and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running Al experiments at scale, versioning, delivery to production, reproducibility and data access.
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How to Save Costs (& Time) on Bringing AI to Production - MLOps Live #2 - With Quadient

May 31, 2020 By Iguazio In Iguazio
The session — featuring Jason Evans, Director of DXP Innovation at Quadient, and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running AI experiments at scale, versioning, delivery to production, reproducibility and data access.
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Git-Based CI CD for Machine Learning & MLOps - MLOps Live #3 - With Microsoft & GitHub

May 31, 2020 By Iguazio In Iguazio
The session — featuring David Aronchick, Head of OSS ML Strategy at Microsoft; Marvin Buss, Azure Customer Engineer at Microsoft; Zander Matheson, Senior Data Scientist at GitHub; and Yaron Haviv, Co-Founder and CTO at Iguazio — goes beyond theory, with industry leaders sharing challenges and practical solutions that involve running AI experiments at scale, versioning, delivery to production, reproducibility, and data access.
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MLOps Automation From A to Z | Jupyter + KubeFlow + MLRun + Nuclio

Apr 12, 2020 By Iguazio In Iguazio
Short but comprehensive end-to-end pipeline demo using the Iguazio real-time data science platform. MLOps (also known as DevOps for machine learning) is the practice of collaboration and communication between data scientists and data engineers to help manage the production machine learning (ML) lifecycle. Presented by Yaron Haviv, CTO & Co-Founder of Iguazio.
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honeybadger

Why Every Web Developer Should Explore Machine Learning

Mar 18, 2020 By Julie Kent In Honeybadger

If software's been eating the world for the past twenty years, it's safe to say machine learning has been eating it for the past five. But what exactly is machine learning? Why should a web developer care? This article by Julie Kent answers these questions. I don't have kids yet, but when I do, I want them to learn two things: Whether or not you believe that the singularity is near, there's no denying that the world runs on data.

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