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RL Presentation: Finding and Executing Reinforcement Learning Projects

RL Presentation: Finding and Executing Reinforcement Learning Projects

Tue Nov 22, 2022, by Phil Winder, in Reinforcement Learning, Talk

Learn about the framework that we use to help organizations find and develop problems that are best suited to reinforcement learning. This includes information about how to find business problems that are suited to RL, how to derisk the development process, and what technical tasks are involved.

Do you like DAGs? Implementing Graph Executor for Bacalhau

Do you like DAGs? Implementing Graph Executor for Bacalhau

Tue Jan 24, 2023, by Enrico Rotundo, in MLOps, Talk, Case Study

When: Tue Jan 24, 2023 at 16:30 UTC Where: Linkedin Live Enrico Rotundo shares experiences of Winder.AI’s AI product consulting experience at a variety of large and small organizations. Learn more about his latest work designing and implementing a directed acyclic graph (DAG) executor for Bacalhau, a decentralised compute platform. You will learn what DAGs are and why they are useful in a machine learning context.

Buildpacks - The Ultimate Machine Learning Container

Buildpacks - The Ultimate Machine Learning Container

Thu Jul 14, 2022, by Enrico Rotundo, Phil Winder, in Case Study, Mlops, Cloud-Native, Talk

Winder.AI worked with Grid.AI (now Lightning.ai) to investigate how Buildpacks can minimize the number of base containers required to run a modern platform. A summary of this work includes: Researching Buildpack best practices and adapting to modern machine learning workloads Reduce user burden and reduce maintenance costs by developing Buildpacks ready for production use Reporting and training on how Buildpacks can be leveraged in the future The video below presents this work.

MLOps Presentation: When do You Need an MLOps Platform Team?

MLOps Presentation: When do You Need an MLOps Platform Team?

Wed May 11, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he presents industry observations of MLOps team size and structure for a range of business sizes and domains. Learn more about how others structure their MLOps teams. Discover which problems you need to solve first. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.

MLOps Presentation: Databricks vs. Pachyderm

MLOps Presentation: Databricks vs. Pachyderm

Wed Apr 6, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he presents a white paper that discusses the differences between two leaders in the data engineering space – Databricks and Pachyderm. Learn how these two products differ, when to use each, and the pros and cons. At the end of the talk Phil distils this information and presets best practices.

Machine Learning Presentation: Packaging Your Models

Machine Learning Presentation: Packaging Your Models

Wed Mar 16, 2022, by Phil Winder, in Machine Learning, MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s machine learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on packaging ML models for production serving. Learn about how the cloud vendors compare, what orchestration abstractions prefer, and how packaging tools seek to find the right abstractions. At the end of the talk Phil distils this information and presets best practices. There’s also some discussion of future trends and some ideas for aspiring open-source engineers.

Machine Learning Presentation: Provenance and Lineage for Data, Pipelines, and Deployments

Machine Learning Presentation: Provenance and Lineage for Data, Pipelines, and Deployments

Wed Feb 16, 2022, by Phil Winder, in Machine Learning, Talk

Dr. Phil Winder shares experiences of Winder.AI’s machine learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on how provenance and lineage, typically thought of as a model deployment problem, can help make the development of machine learning models more repeatable, understandable, and robust. Discover the difference between lineage and provenance. Learn how to determine the “strength” of your lineage and how robust it is to failure.

Reinforcement Learning Presentation: Cyber Security

Reinforcement Learning Presentation: Cyber Security

Wed Jan 19, 2022, by Phil Winder, in Reinforcement Learning, Talk

Dr. Phil Winder shares experiences of Winder.AI’s reinforcement learning consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on RL applications, looking at the use of RL in cyber security and discusses one interesting case study about how Winder.AI helped an internal security team develop a tool to hack web application firewalls. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.

MLOps Presentation: How to Build Resilient AI With GitOps

MLOps Presentation: How to Build Resilient AI With GitOps

Wed Jan 12, 2022, by Phil Winder, in MLOps, Talk

Dr. Phil Winder shares experiences of Winder.AI’s MLOps consulting experience at a variety of large and small organizations. Abstract In this talk he focuses on how GitOps is a key ingredient in any ML platform to enhance resiliency and observability. Learn why it is important, what it involves, and how to implement it in this short 30 minute video. About This Series Welcome to Winder.AI talks. A series of free interactive webinars hosted by Dr Phil Winder, CEO of Winder.

CloudNativeX Interview: Reinforcement Learning

CloudNativeX Interview: Reinforcement Learning

Mon Apr 5, 2021, in Reinforcement Learning, Talk

Join Lee Razo and Phil Winder for this comprehensive introduction to Reinforcement Learning, an area of machine learning in which problems are tackled with intelligent agents which take actions to maximize a specified reward. Phil (quite literally) wrote the book on this topic and he takes us through the fundamentals of RL, some common use cases as well as tips on how even a small or mid-sized company can get started with and benefit from RL.