Data-centric AI marks a dramatic shift from how we’ve done AI over the last decade. Instead of solving challenges with better algorithms, we focus on systematically engineering our data to get better and better predictions. But how does that work in the real world? It’s one thing to define data-centric AI but it’s another thing altogether to make the shift to a data centric approach. In this talk I’ll walk you through how to solve problems right in the data, with data augmentation, synthetic data, re-labeling and more. You’ll learn how to shift your mindset to creatively solving problems in the data instead of looking for magical fixes from yet another new model. Pachyderm is cost-effective at scale, enabling data engineering teams to automate complex pipelines with sophisticated data transformations across any type of data. Our unique approach provides parallelized processing of multi-stage, language-agnostic pipelines with data versioning and data lineage tracking. Pachyderm delivers the ultimate CI/CD engine for data.
This blog has been republished by AIIA. To view the original article, please click HERE.
Recent Comments