Talk

Industrial insight and articles from Winder.AI, focusing on the topic Talk

MLOps Presentation: Databricks vs. Pachyderm

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Author
Dr. Phil Winder
CEO

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.

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Machine Learning Presentation: Packaging Your Models

Published
Author
Dr. Phil Winder
CEO

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.

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

Published
Author
Dr. Phil Winder
CEO

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.

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Reinforcement Learning Presentation: Cyber Security

Published
Author
Dr. Phil Winder
CEO

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.

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MLOps Presentation: How to Build Resilient AI With GitOps

Published
Author
Dr. Phil Winder
CEO

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.

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CloudNativeX Interview: Reinforcement Learning

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Author

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.

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InfoQ Podcast: Phil Winder on the History, Practical Application, and Ethics of Reinforcement Learning

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Author

InfoQ · Phil Winder on the History, Practical Application, and Ethics of Reinforcement Learning Charles Humble, friend and editor of InfoQ, was kind enough to ask me for an interview to talk more about my new book, in podcast format. From the blurb: In this episode of the InfoQ podcast Dr Phil Winder, CEO of Winder.AI, sits down with InfoQ podcast co-host Charles Humble. They discuss: the history of Reinforcement Learning (RL); the application of RL in fields such as robotics and content discovery; scaling RL models and running them in production; and ethical considerations for RL.

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DataTalksClub - Industrial Applications of Reinforcement Learning

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Author

Reinforcement learning (RL), a sub-discipline of machine learning, has been gaining academic and media notoriety after hyped marketing “reveals” of agents playing various games. But these hide the fact that RL is immensely useful in many practical, industrial situations where hand-coding strategies or policies would be impractical or sub-optimal. Following the theme of my new book (https://rl-book.com​), I present a rebuttal to the hyperbole by analysing five different industrial case studies from a variety of sectors.

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GOTO Book Club: How to Leverage Reinforcement Learning

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Author

In this episode of GOTO’s book club I speak to Rebecca Nugent, Feinberg professor of statistics and data science at Carnegie Mellon univeristy. We talk, at length, about the application of reinforcment learning, specifically how it could be a way of creating truly personalised teaching curricula. It’s a really interesting discussion and it’s great to get someone of Rebecca’s calibre to bounce ideas off.

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A Code-Driven Introduction to Reinforcement Learning

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Notebook link Abstract Reinforcement learning (RL) is lined up to become the hottest new artificial intelligence paradigm in the next few years. Building upon machine learning, reinforcement learning has the potential to automate strategic-level thinking in industry. In this presentation I present a code-driven introduction to RL, where you will explore a fundamental framework called the Markov decision process (MDP) and learn how to build an RL algorithm to solve it.

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