Abstract: Open source is constantly evolving to drive innovation in the ML and AI ecosystems. As ML and AI users, data engineers and data scientists, you're often faced with the decision of whether to build or buy the tools for your ML and AI workloads. In this talk, we'll explore how open-source platforms empower HPE to collaborate and customize our approach to help users with the unique challenges they face and consistently achieve optimal results.
We'll take a look at the HPE Software that is built by integrating popular open source ML and AI tools that users are often building and managing themselves. These tools help streamline complex processes and promote collaboration, revolutionizing HPE's approach to data science. With open-source integration, we can create end-to-end solutions for data, analytics, and AI. From diverse, distributed multi-format data to data preparation, model training, tuning, deployment, and monitoring, we'll cover the entire AI lifecycle.
Join us as we explore how these powerful open source tools reshape the way we work, turning raw data into actionable insights faster than ever before. For data engineers and data scientists, this seamless journey empowers you to make a real impact in your organizations. Whether you're building or buying, let's unlock the full potential of open source and revolutionize the ML and AI ecosystem together.
That building or buying your AI and ML tools comes with pros and cons. While this is NOT a product pitch it's to highlight there are many platforms out there that are integrating popular open source tools to create a platform for data scientist and data engineers. We want the audience to know what to look for and how to decide whether they want to build vs. buy.
Bio: Bio Coming Soon!