Pachyderm ❤️ Spark ❤️ MLFlow - Scalable Machine Learning Provenance and Tracking
Learn how we integrated Pachyderm with Spark and MLFlow for scalable ML tracking.
Enrico Rotundo
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10 minMore articles
Page 9 of 21
Enrico Rotundo
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10 min
Optimising Industrial Processes with Reinforcement Learning
In this case study, we will discuss the use of reinforcement learning to optimise industrial processes. Find out how to use reinforcement learning to automate procedures that are time-consuming and difficult to understand.
Dr. Phil Winder
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3 min
Buildpacks - The Ultimate Machine Learning Container
Buildpacks enable MLOps platform teams to reduce the maintenance burden of shared containers. Learn how Winder.AI helped Lightning AI develop Buildpacks for their service.
Enrico Rotundo
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14 min
A Comparison of Computational Frameworks: Spark, Dask, Snowflake, more
Learn more about the current state of the art general purpose computation platforms in this landscape analysis. This is a case study of a project completed by Winder.AI for Protocol Labs.
Enrico Rotundo
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5 min
Save 80% of Your Machine Learning Training Bill on Kubernetes
Kubernetes' cluster auto-scaler allows for the scale out of large machine learning jobs. But which cloud you use, and what settings you provide, make a massive difference. Learn how we helped one client save 80% off their bill.
Dr. Phil Winder
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13 min
MLOps Presentation: When do You Need an MLOps Platform Team?
Dr. Phil Winder presents industry observations of MLOps team size and structure for a range of business sizes and domains.
Dr. Phil Winder
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1 min
MLOps Presentation: Databricks vs. Pachyderm
This talk discusses presents our comparison of two leaders in the engineering space -- Databricks and Pachyderm.
Dr. Phil Winder
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1 min
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
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 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 minNewsletter
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Case studies and industry analysis from our team. No hype, roughly monthly.