• Back-end programming: making your applications cloud ready

    High Tech Campus Eindhoven

    In collaboration with ISAAC (https://bit.ly/2lETIe3), we want to invite you to share your experience and questions about making your applications cloud ready for the changing world. Agenda: 18:30 Doors open + 🍔🍔🍔 19:00 💬1: Jan-Willem Mulder 19:35 Short break 19:45 💬2: Ruud Zwakenburg 20:20 Short break 20:30 💬3: Dennis Abrazhevich 21:15 End + drinks Jan-Willem Mulder: TD @ ISAAC: CI/CD with containers from a Java developer perspective Bio: Being a specialist in the field of automation and CI / CD, Jan-Willem steers the project teams of ISAAC’s Java Chapter with regards to design and the development of solutions. As ISAACs Technical Director, Jan-Willem ensures the teams are challenged with fun, interesting and complex projects. He also guides several Guilds linked to technology innovation within ISAAC. Ruud Zwakenburg: Senior Solution Architect @ Red Hat: Supersonic Subatomic Java Bio: He is a Solution Architect at Red Hat and has many years of experience in system development, integration, middleware and nowadays, also container-native application development. Dennis Abrazhevich: Solution Architect: Serverless approach for reducing complexity Bio: Dennis is an AWS cloud consultant and architect with years of experience in solution and systems design and integration. His projects involve devops automation, CI/CD, data ETL, analytics and big data lake. Professional interests are in the functional Clojure platform, reducing complexity of system development by modernising architecture, technical maturity and automation. He worked in domains of digital on-demand television, health systems, online gaming, digital/online marketing and academia. Dennis’ personal interest are reading, tennis, music- and filmmaking. Can't talk Server Side Solutions on an empty stomach -> some food and drinks are provided! The evening will finish of with time for drinks and chats. Hope to meet you there!

  • Exposing Machine Learning Models as a Microservice

    De Nieuwe Poort

    In Collaboration with Visser & van Baars (https://www.visservanbaars.nl), we want to invite you to share your experience and questions about Microservices Architecture and Machine Learning/AI. Program 18:30 Doors open + 🍔🍔🍔 19:00 Speaker 1 19:45 Break 20:00 Speaker 2 20:45 End + drinks Microservices Architecture and Machine Learning/AI are two popular topics nowadays. So how can we place ML models into Microservices Architecture? Each service in Microservices Architecture can expose APIs to serve its consumers. API development is a separate expertise and can be challenging for Data Scientists as well as Data Engineers. Often companies hire Data Scientists to analyze data and build ML models. They also hire Data Engineers to set up data infrastructure for efficiently collecting, processing and storing data pipelines. After setting up the data infrastructure and building models next step is to industrialize those models. There are several different ways of industrialization. A model could be deployed in a batch mode to do one off predictions or can be integrated into streaming applications to do continuous near real-time predictions. Another way to industrialize is deploying ML models as an API for on-demand predictions. In this demo presentation we will talk about industrialization of ML models in general and show you how you can build an API to expose your model. Volkan Dogan: I am a software engineer and trainer with almost 15 years of hands-on experience in designing, developing and maintaining Low Latency, High Availability, scalable software applications. I moved to the Netherlands 12 years ago from Turkey. I had worked as a Freelance software engineer for about 3,5 years before I started Pivot Horizon as a Co-Founder. Dennis de Weerdt: I am a recently graduated software engineer from the Netherlands, with a specialization in machine learning and formal verification. I obtained by Master's degree in Denmark. I joined Pivot Horizon in August this year, and seek to develop myself as a professional skilled in both data science and data engineering.