As part of a collaborative initiative, Trifork and GOTO have organized a series of events with GOTO experts and Trifork Software Engineers & Architects.
Join us in this online Meetup with Trifork’s Software Engineer, Ewan Henry, hosting GOTO expert, Adi Polak. During this one hour session, Adi will focus on the importance of data, how it impacts machine learning in the industry and how Apache Spark helps us solve most of it. The presentation will be followed by a Q&A session and the opportunity to network with other like-minded attendees.
With the buzz about all the latest advances in machine learning, data scientists are in high demand. All companies want to innovate by developing recommendation systems, fraud detection, sentiment analysis, and more. We sometimes forget about the backbone of it all, the one that fuels the machine learning engine, data. How does data impact our machine learning performance, and what are the known problems? It’s time to talk about overfitting, big data, and advanced tools such as Apache Spark.
Join this session to learn about the importance of data, how it impacts machine learning in the industry and how Apache Spark helps us solve most of it!
17:00 | Welcome to this online Meetup from Trifork host
17:05 | Adi Polak will present her subject of the day
17:35 | Live Q&A with Adi Polak
17:55 | Thank you for joining us for this online Meetup
Trifork, Software Engineer
Ewan started his career in software engineering at Trifork Amsterdam in 2018, taking a sizeable lateral step from work as a scientific researcher. He has learnt a great deal about software development since then and has enjoyed working in a broad variety of roles: From front and back end development in enterprise applications, to mobile app development in the healthcare sector, with some machine learning engineering thrown in for good measure. When not behind a keyboard, Ewan enjoys cooking and is always keen to challenge the unfavorable stereotypes about British cuisine!
Microsoft, GOTO Expert
Adi Polak is a Sr. Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft. Her work focuses on distributed systems, big data analysis, and scalable machine learning. In her advocacy work, she brings her vast industry research & engineering experience to bear in educating and helping teams design, architect, and build cost-effective software and infrastructure solutions that emphasize scalability, team expertise, and business goals. Adi is a frequent presenter at worldwide industry conferences, O’Reilly author, and technical instructor. When Adi isn’t building Machine Learning Pipelines or thinking up new software architecture, you can find her hiking and camping in nature.