Here at Cloudera, we’re committed to helping make the lives of data practitioners as painless as possible. For data scientists, we continue to provide new Applied Machine Learning Prototypes (AMPs), which are open source and available on GitHub. These pre-built reference examples are complete end-to-end data science projects. In Cloudera Machine Learning (CML), you can deploy them with the single click of a button, bringing data scientists that much closer to providing value.
SAP’s library of pre-defined reports for Finance and Controlling (FICO) is great for addressing some of the core tasks associated with finance and accounting. Those reports align well with accounting standards under GAAP and IFRS. Unfortunately, they rarely do a good job of addressing the kind of reporting needed to make informed managerial decisions.
As a very hands-on VP of Product, I have many, many conversations with enterprise data science teams who are in the process of developing their MLOps practice. Almost every customer I meet is in some stage of developing an ML-based application. Some are just at the beginning of their journey while others are already heavily invested. It’s fascinating to see how data science, a once commonly used buzz word, is becoming a real and practical strategy for almost any company.
GraphQL is a solid alternative to a traditional REST API, and offering one to your users may be easier than you think. Follow along as Kevin Cunningham builds a GraphQL endpoint with Node.js and MongoDB!
TL;DR: Setting up CI/CD pipelines for games made with the Godot engine is quite simple, thanks to the fact that it’s easy to work with Godot using the command-line interface. This means we can quickly install Godot on a Codemagic build machine and automate the export of Godot games, though we’ll need to specify some configurations as well. Let’s see how to automate Godot game projects! These past few months, I’ve talked about using Codemagic to build and publish Unity games.