Tabular Learning

While tabular data is central to all organizations, it seems left out of the AI discussion focused on images, text, and sound. For data science, most of the excitement is in machine learning, but most of the work has happened before. Tables often require extensive manual transformation or "data wrangling". Gaël Varoquaux, research director at Inria and co-founder at scikit-learn & Probabl will discuss how he progressively rethought this process, building machine-learning tools that require less wrangling. You will build a new library, skrub (https://skrub-data.org), that facilitates complex tabular learning pipelines, writing, as much as, possible wrangling as high-level operations, and automating them. A few lines of skrub can spare you dozens of wrangling lines! Want to stay ahead on AI? Then subscribe to ODSC today 🚀🧠- https://www.youtube.com/c/OpenDataScienceCon?sub_confirmation=1 You can also follow ODSC on: LinkedIn - https://www.linkedin.com/company/open-data-science/ Twitter - https://twitter.com/_odsc Facebook - https://www.facebook.com/OPENDATASCI/ Medium - https://odsc.medium.com/