- Deep Learning: Practical Use Cases
Join us for a deep dive into practical use cases for deep learning! Presentation #1: AI Meets Mail Processing by Denis Maciel, Data Scientist at Dataiku In an effort to bring AI to mail processing, Denis will present a prototype we've developed for a client in the insurance industry. Using Computer Vision and Deep Learning techniques, it automatically processes typed and hand-written letters to send them to the correct department within the organization. Denis Maciel, Data Scientist at Dataiku: Earlier in his career, Denis has helped various startups in Berlin to build their analytics infrastructure. An economist by training, Denis often finds himself contemplating causal inference problems in massive datasets. Give him messy data and he will have an amazing time wrestling with it. Presentation #2: Machine Learning and Deep Learning in Networking by Eduard Dulharu, Senior Network Architect at AT&T: Eduard will present his research on using Machine Learning and Deep Learning to increase resiliency and performance in the field of networking. This is especially important in critical IP networks, where networking performance can make a difference between winning or losing (e.g. financial trading systems), or between high quality and mediocre healthcare services (e.g. hospital networks). Eduard Dulharu, Senior Network Architect at AT&T: Eduard started his career at the Romanian Ministry of National Defense before moving to the telecommunications industry, where he evolved as a network engineer. He holds an MsC in IT Security and is passionate about applying new Machine Learning and Deep Learning technologies to IP networks. Timeline: 6:30 PM: Pizza, beer, & networking 7:00 PM: AI Meets Mail Processing by Denis Maciel, Data Scientist at Dataiku 7:30 PM: Machine Learning and Deep Learning in Networking by Eduard Dulharu, Senior Network Architect at AT&T 8:00 PM: More beer & networking!
- Machines and Machine Learning: AI in Manufacturing
Join us for a meetup on AI in Manufacturing with Caroline Kleist, Head of Analytics at Mayato, and Fredrik Ström, Technical Alliances Manager at Dataiku. Introduction by Fredrik Ström, Technical Alliances Manager at Dataiku Interactive segment about: Applied Magic: Real Data Science Solutions in Everyday Use Fredrik Ström, Technical Alliances Manager at Dataiku: Like many, Fredrik started grappling with bigger datasets while in digital marketing and web development. International Background both in big and small corporations, line and project and crowd-work, change management and team culture changes (joint venture, start-ups). Deep into Applied Magic: Real Data Science Solutions in Everyday Use by Caroline Kleist, Head of Analytics at Mayato In this talk, we want to report about the typical course of AI projects and further relevant use cases in companies within manufacturing branches. Although, the buzzword ‘’predictive maintenance“ is on everyone’s lips, there still do not exist best practices on the market. Therefore, we want to summarize common challenges during their implementation and how you can overcome them. Especially, collaboration and interdisciplinary teams are key factors for success - And Dataiku is perfectly supporting this mission. Caroline Kleist, Head of Analytics at Mayato: As a data science expert, she holds a Master of Science degree in statistics and has extensive project experience. She is experienced in overseeing the implementation and establishment of advanced analytics methods at companies from a wide range of industries, as well as in implementing data science projects – from customer analytics projects and recommendation engines to streaming data analytics for predictive maintenance. Timeline: 6:30 PM: Pizza, beer, & networking 7:00 PM: Introduction by Fredrik Ström, Technical Alliances Manager at Dataiku 7:30 PM: Talk by Caroline Kleist, Head of Analytics at Mayato 8:00 PM: More pizza, beer, & networking