At NoRedInk we had a normal React code base. That is, until we tried Elm – a purely functional language that compiles to JavaScript. A couple years and a couple hundred thousand lines of Elm code later, we found ourselves with a lot more users and no runtime exceptions in the production logs from our Elm code. Lots of companies dabble in functional programming, but most code in the world today is imperative. In contrast, the NoRedInk story is one of a successful business built on pure functional programming: today essentially our entire frontend is Elm, and the majority of our traffic is handled by a Haskell service on the back-end.This talk is partly about what these technologies are – so don’t worry if they’re unfamiliar! – and partly about why and how we successfully adopted them. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=gRFjOo-ZgK8&t=223s https://www.youtube.com/watch?v=bpBeRnyqaIQ

Learn about the key CSS layout methods of flexbox and grid. Discover how these layout methods enable responsive, content-aware designs, and how to choose the best layout method for the component you need to build. Resources: https://noti.st/rachelandrew/IQsXZC/css-layout-workshop PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=yMEjLBKyvEg https://www.youtube.com/watch?v=EmwjBKNX0Rc

Check out Ville Tuulos's book 📚 Effective Data Science Infrastructure | http://mng.bz/BxRJ 📚 To get 40% discount on this book use the discount code ⭐ WATCHTUUL40 ⭐ In this video, Ville demonstrates how to develop and deploy a production-grade ML application on the fly, using tips and techniques presented in his book, Effective Data Science Infrastructure. 📚📚📚
Effective Data Science Infrastructure | http://mng.bz/BxRJ To save 40% off this book use discount code: watchtuulos40 📚📚📚 About the book:
Effective Data Science Infrastructure: How to make data scientists more productive is a guide to building infrastructure that will supercharge data science projects and data scientists. Based on state-of-the-art practices that power the massive data operations of Netflix, this book offers techniques and patterns relevant to companies of all shapes and sizes. You’ll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. As you work through this easy-to-follow guide, you’ll set up end-to-end infrastructure from the ground up, with a fully customizable process you can easily adapt to your company. You’ll build a cloud-based development environment that covers local prototyping and deployment to production, set up infrastructure that supports a real-world machine learning application, and handle a large-scale application for processing hundreds of gigabytes of data. Throughout, you’ll follow a human-centric approach focused on user experience and meeting the unique needs of data scientists. https://www.youtube.com/watch?v=GU6IuFpYYN8