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 minArticles in this topic
Page 3 of 3
Enrico Rotundo
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18 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
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 min
Unit Testing Data: What is it and how do you do it?
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
Building an Enterprise NLP Platform
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 min
A Simple Docker-Based Workflow for Deploying a Machine Learning Model
Deploying ML models is hard, right? Not with this Docker-based workflow!
Dr. Phil Winder
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7 minDevOps and Data Science: DataDevOps?
DataDevOps or often just DataOps, is the combination of DevOps and Data Science. The goal is to empower Data Scientists to build reliable software. The downside, you need to be an expert at everything! Read more.
Dr. Phil Winder
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8 minNewsletter
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Case studies and industry analysis from our team. No hype, roughly monthly.