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Google Cloud Architecture Kata
2024-04-18 · 17:00
An architecture kata is an exercise in practising architecting a system in a safe environment, learning about other perspectives, and building your skills before an actual project. Everyone, from complete novices to experienced architects, is welcome. In this workshop, we will focus on solutions with Google Cloud technologies. Everything is on paper, so you don’t even need a laptop. THIS IS AN INVITE ONLY EVENT, FILL IN THE FORM WE WILL NOTIFY THE ATTENDEES BASED ON SELECTION. https://forms.gle/BUJHXKGKjxZgfYoh7 Agenda 6:00 pm Arrival, pizza and networking 6:30 pm Workshop briefing and team formation 6:40 pm Design starts 7:40 pm Presentations begin 8:10 pm Retrospective and wrap-up 8:30 pm Leave the building Facilitators Daniel Vaughan is a Cloud Architect at Mastercard, Google Cloud Innovator Champion and author of O’Reilly’s Cloud Native Development with Google Cloud. Agenda Hosted By Renuka Kelkar, GDG Organizer Sumith Damodaran, PM / GDG Organizer Jai Campbell, Senior Architect / GDG Organizer Chris Bouloumpasis, GDG Organizer Goran Minov, Team Lead | GDG Organizer Inès Rigaud, GDG Organizer chinmayee murugkar, GDG Organizer Complete your event RSVP here: https://gdg.community.dev/events/details/google-gdg-london-presents-google-cloud-architecture-kata/. |
Google Cloud Architecture Kata
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Data Science: The Hard Parts
2023-11-01
Daniel Vaughan
– author
This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly). |
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Analytical Skills for AI and Data Science
2020-05-21
Daniel Vaughan
– author
While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies |
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