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Integrating Data to Build Emotional Health: How SU Queensland Uses Talend to Enrich Service Delivery

The mission statement is so direct and uncomplicated. SU Queensland, a non-profit organization based in Australia, is all about “bringing hope to a young generation.” The realities of delivering on this charter, of course, are multi-dimensional and complex. SU Queensland provides a wide range of services to schools, churches, and community groups across Australia, including youth camps, school chaplains, community engagement programs, and training and support for youth workers.

Operationalizing Machine Learning for the Automotive Future

It’s no secret that global mobility ecosystems are changing rapidly. Like so many other industries, automakers are experiencing massive technology-driven shifts. The automobile itself drove radical societal changes in the 20th century, and current technological shifts are again quickly restructuring the way we think about transportation. The rapid progress in AI/ML has propelled the emergence of new mobility application scenarios that were unthinkable just a few years ago.

Delivering Modern Enterprise Data Engineering with Cloudera Data Engineering on Azure

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. CDP Data Engineering offers an all-inclusive toolset that enables data pipeline orchestration, automation, advanced monitoring, visual profiling, and a comprehensive management toolset for streamlining ETL processes and making complex data actionable across your analytic teams.

A CDO's Field Guide to Finding Value in Data

A proverb from the Democratic Republic of the Congo says, “A good chief is like a forest: Everyone can go there and get something.” And, a Chief Data Officer is no exception. According to Forrester Research published in January 2021, data leaders today face a broad mandate as the role has expanded over the years. In the early years, CDOs mostly reported to technology leaders.

[MLOps] The Clear SHOW - S02E11 - DIY Strikes Back! Building the Model Store!

Ariel extends ClearML's "experiment first" approach towards a "model first" approach - by building a model store. See how easy it is to add metadata to the model artifacts. + Colab notebook (uses the demo server, just run it and see what happens) ClearML is the only open-source tool to manage all your MLOps in a unified and robust platform providing collaborative experiment management, powerful orchestration, easy-to-build data stores, and one-click model deployment.

Online Meetup: Kong Gateway 2.5 Release

In this session, we get you up-to-speed on the Kong Gateway 2.5 release with a summary of the features and news, including: Kong’s Online Meetups are a place to learn about technologies within the Kong #opensource ecosystem. This interactive forum will give you the chance to ask our engineers questions and get ramped up on information relevant to your #Kong journey.

Software QA Jobs | Software QA Walkins | Software QA Internships | Qualitician.com

Qualitician is the leading global career site for professionals working in the software testing domain. Set up your profile, apply to software qa jobs, see where you are along the application process, quickly follow up with employers, and let recruiters find you fast. We’re growing quickly and adding new software qa opportunities every day. Explore open software qa roles to find a position that's right for you. Find your next dream software qa job here!

How to add performance testing to CI/CD pipelines using k6 and GitHub Actions

Nicole van der Hoeven shows how to add performance testing to a CI/CD pipeline from scratch and for free, using k6 to write a test script and GitHub Actions to automate it. She also talks about how to set it up using k6 Cloud and why the extra cost might be justified. OTHER CI/CD TOOLS.

[MLOPS] From #GTC21: Best Practices in Handling Machine Learning Pipelines on DGX Clusters

Learn how to set up and orchestrate end-to-end ML pipelines, leveraging large DGX clusters. We'll demonstrate how to orchestrate your training and inference workloads on DGX clusters, with optional setup of remote development environments leveraging the multi-instance GPUs on the NVIDIA A100. We'll also show how pipelines can be built to serve both research and deployment workloads, all while leveraging the compute inherent in the DGX cluster.