To honor ten years of PyData London, join Dr. Rebecca Bilbro as she takes us back in time to reflect on a little over ten years working as a data scientist. One of the many renegade PhDs who joined the fledgling field of data science of the 2010's, Rebecca will share lessons learned the hard way, often from watching data science projects go sideways and learning to fix broken things. Through the lens of these canon events, she'll identify some of the antipatterns and red flags she's learned to steer around.

She'll also talk about how her practice of data science has changed over time, and share a handful of fairly generalizable techniques that work for her, her students, and her engineering team at Rotational Labs.

Prior Knowledge Expected –
No previous knowledge expected

Dr. Rebecca Bilbro
A pioneer of the data science revolution in the early 2010’s, Dr. Rebecca Bilbro is an applied AI/ML engineer, teacher, and author. Rebecca (aka @Elder_Data_Scientist on TikTok) is the cocreator of Yellowbrick, a Python library that integrates the scikitlearn and matplotlib APIs to support more convenient model diagnostics and steering. As cofounder and CTO of Rotational Labs (rotational.io), Rebecca is motivated by a desire to unite the data science and engineering communities. She and her team help other companies leverage inhouse domain expertise and data to build and deploy LLMs, data products, and services. Rebecca earned her doctorate from the University of Illinois, UrbanaChampaign, where her research centered on domainspecific languages within engineering.

PyData
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LinkedIn:   / pydataglobal  
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PyData is an educational program of NumFOCUS, a 501(c)3 nonprofit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and communitydriven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cuttingedge use cases.

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