GitOps for Machine Learning Projects
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 minMore articles
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Dr. Phil Winder
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13 min
Machine Learning Presentation: Provenance and Lineage for Data, Pipelines, and Deployments
Learn the difference between lineage and provenance. Discover the different strengths of lineage. Find out how you can decompose your AI projects to make your machine learning models more repeatable, understandable, and robust.
Dr. Phil Winder
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1 min
Databricks vs Pachyderm - A Data Engineering Comparison
Databricks vs. Pachyderm - two leading data engineering products. Find out how they compare in this white paper.
Enrico Rotundo
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18 min
Reinforcement Learning Presentation: Cyber Security
A talk about the use of RL in cyber security including a case study about how Winder.AI helped an internal security team develop a tool to hack web application firewalls.
Dr. Phil Winder
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1 min
MLOps Presentation: How to Build Resilient AI With GitOps
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
The Value of a Machine Learning Pipeline: Past, Present, and the Future of MLOps With Kubeflow
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
Using Reinforcement Learning to Attack Web Application Firewalls
This case study explains how Winder.AI, an ML/RL/MLOps consultancy, worked with the cyber security team at a multinational food and beverage company to research, design, and implement a reinforcement learning based agent capable of hacking web application firewalls (WAF). Find out more.
Dr. Phil Winder
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7 min
Helping Modzy Build an ML Platform
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
How To Build a Robust ML Workflow With Pachyderm and Seldon
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
How We Built an MLOps Platform Into Grafana
A case-study investigating how Winder.AI built an MLOps platform into Grafana.
Dr. Phil Winder
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3 minNewsletter
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