
Machine Learning Presentation: Packaging Your Models
This talk discusses common ways to package your machine learning models. Learn about best practice and the current state-of-the-art.
Dr. Phil Winder
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1 min
This talk discusses common ways to package your machine learning models. Learn about best practice and the current state-of-the-art.
Dr. Phil Winder
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1 min
Learn how GitOps, the practice of being declarative, can help your artificial intelligence project development process become faster and more resilient.
Dr. Phil Winder
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13 min
Databricks vs. Pachyderm - two leading data engineering products. Find out how they compare in this white paper.
Enrico Rotundo
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19 min
Learn how GitOps for AI is a key ingredient in any ML platform to enhance resiliency and observability.
Dr. Phil Winder
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1 min
Kubeflow is an incredible project, and Kubeflow pipelines have become the defacto open-source pipelining solution for machine learning pipelines. But it's not good enough and we need to move past it. Learn why and how.
Dr. Phil Winder
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11 min
Modzy asked Winder.AI to help improve their ML platform with the addition of MLOps management and monitoring capabilities. During this work we also collaborated on two new open source projects. We provided ML and MLOps development expertise to deliver rapid results. Find out more.
Dr. Phil Winder
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4 min
This article accompanies our demonstration of using Pachyderm and Seldon Deploy to manage the machine learning lifecycle. Follow along with the fictional organization CreditCo on a journey of ML failure and robustness. Learn how Winder.AI can provide MLOps consulting to help make your ML workflows more robust.
Enrico Rotundo
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9 min
A case-study investigating how Winder.AI built an MLOps platform into Grafana.
Dr. Phil Winder
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3 min
Reap the benefits of your raw data through learning the importance of unit testing, how to apply it, and what tools to use for enhanced data quality.
Hajar Khizou
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8 min
Learn how Winder.AI delivered an NLP platform to a large enterprise in the oil and gas industry.
Dr. Phil Winder
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3 minCase studies and industry analysis from our team. No hype, roughly monthly.