05-03, 15:30–15:55 (Asia/Jerusalem), PyData Track 2
AutoML is a python driven tool we built in Outbrain Recommendations group. In this talk we'll share motivation for creating this tool, describe the general architecture and do a live short demo.
Recently Outbrain CTR prediction system was heavily reworked. In this talk, we will share our key enabler in this journey, a Python-based AutoML engine which allows data scientists to perform faster offline research iterations. This tool is a robust and highly parallel search engine built solely in Python. In this talk we'll share the motivation for building this tool, go through the general architecture and showcases some of its capabilities in a live demo.
Hebrew
Target audience –Developers, Data Scientists, R&D, Managers
Software Engineer, Data Scientist, Cyclist. Yield Optimization Manager at Outbrain
For the past decade Hila has been processing, analyzing and generating algorithms. After earning her masters (summa cum laude) at BIU NLP and publishing at elite academic venues such as EMNLP, she began to research & develop algorithms that analyze call center calls as a senior researcher at NICE. During that time she published 4 US patents and academic posters at various venues. For the past 1.5 years she has been working as a senior data scientist at Outbrain where she works on large-scale super-fast algorithms for the native ads field. Hila also loves to teach and share her experience and has talked at various meetups and conferences.