At our very first KNIME meetup in Budapest, Jon Fuller (KNIME) will show how KNIME, Apache Spark and Microsoft Azure / Amazon AWS can enable fast, cheap and automated classification of digital images. Working with KNIME Analytics Platform, we use KNIME on Apache Spark running on an HDInsight cluster to pre-process the image data and then train a deep convolutional neural network on GPU-enabled VMs to classify the images. The trained model is easily deployed to end-users as a web application using the KNIME WebPortal.
There will be two talks from EPAM. The first, "Open Source Recommender" is about leveraging Python to create product recommendation engines in KNIME and will be presented by Máté Kormos. "Scaled Data Harmonization" is the topic of the second talk by Ákos Tóth and will discuss the global data harmonization of multiple external and internal data sources to achieve an actionable insight on the market inventory level.
- 17.30 Arrivals
- 17:45 "Introduction to KNIME", Mihály Medzihradszky (KNIME)
- 18:00 "Scaled Data Harmonization in KNIME" Ákos Tóth (EPAM)
- 18:30 Break
- 18:45 "Open Source Recommender" Máté Kormos (EPAM)
- 19:05 "Image Analyis with KNIME, Apache, Spark, and the Cloud" Jon Fuller (KNIME)
- 19:35 Networking Time. Drinks & snacks will be provided.
To celebrate this very first KNIME meetup in Budapest, meetup guests are very welcome to join us for an after-meetup drink at Élesztő!
Mihály “Medzi” Medzihradszky is Manager Life Sciences at KNIME and also heavily involved in all things Customer Development. His main interest is understanding the needs of customers and helping them find a solution using KNIME. As a native of Budapest he is also very enthusiastic about building the KNIME community in Hungary. Medzi has an Msc in Economics and has spent the last 8 years in various customer development roles in the R&D and IT industries.
Jon Fuller is an Application Scientist at KNIME and he's responsible for all things cloud at KNIME. He is passionate about showing customers how they can leverage the powerful Advanced Analytics features of the KNIME Analytics Platform and deploy them using the KNIME Server. Jon is experienced at deploying the KNIME Server in both traditional and cloud infrastructures alongside Big Data platforms. Jon holds a PhD, and draws on years of experience as a Bioinformatician, that got him excited by the challenges of data science in the first place.
Máté Kormos is a Data Scientist at EPAM Systems with a keen interest in data mining and statistical computing. He participated in the development of various KNIME solutions for major consumer goods companies and he regularly conducts KNIME training sessions within EPAM both on beginner and advanced level. After obtaining a master's degree in bionic engineering, he spent a few years in computational cancer research, then he moved to the BI sector to find actionable insights and business value in data.
Akos Toth is Lead Business Analyst at EPAM Systems, leading and designing complex BI solutions that involve KNIME. His strengths are automating and scaling out BI solutions globally while tackling various departmental or regional requirements. Akos is keen to find the most efficient way to drive value with his solutions, applying an understanding of the business environment and processes that need to be supported. He has an MSc in Finance and has led BI project teams in FMCG sector in the last 3 years.