The Developer UnConference is an exchange and learning platform for Developers and Non-Developers (really!): IT Architects, Data Scientists, Analysts, Managers... and all interested people in topics like Hacking, Cloud Computing, Data Science, Analytics, Big Data Analytics, Artificial Intelligence, Machine Learning, Blockchain, Research, DevOps, Robotics, Quantum Computung Open Source and other emerging technologies.

This event is free-of-charge. Food and beverages are in general not covered - except indicated.

The main event page is here: https://www.meetup.com/Big-Data-Developers-Switzerland/events/242917086/.

Agenda

TALKS & DEMOS (Auditorium)

1800-1815 Talk 1: "Welcome & Kickoff" (Holger Kyas, IBM Switzerland)

1815-1845 Talk 2:"AI on Structured Data - DeepLearning Neural Networks applied for Anomaly Detection, Time-Series Forecasting and Denoising" (Romeo Kienzler, IBM Switzerland)

1845-1915 Talk 3:"New Neural Network Training Algorithms"(Bojan Ploj, College of Ptuj, Slovenia)

1915-1940 Talk 4: "NLP for Swiss German" (Noëmi Aepli, University of Zurich & Nora Hollenstein, IBM Research Switzerland)

1940-2000 Talk 5: "How AI and NLP are helping to understand Swiss German Dialect" (Jürg Schleier, Spitch AG)

2000-2100 Social Networking & Apéro

DETAILS

Talk 1: "Welcome & Kickoff" (Holger Kyas, IBM Switzerland) [Technical Skill Level: All]

About Holger: Consulting Technical Client Architect@IBM, https://www.linkedin.com/in/holgerkyas/, https://twitter.com/holgerkyas

Talk 2: “AI on Structured Data - DeepLearning Neural Networks applied for Anomaly Detection, Time-Series Forecasting and Denoising” (Romeo Kienzler, IBM Switzerland) [Technical Skill Level: Medium-Advanced]]

Abstract: DeepLearning and Neural Networks are disrupting the AI space. But most people are concentrating on Computer Vision and Natural Language Processing. In this talk we'll tackle down the problems of Advanced Signal processing like de-nosing, anomaly detection and time-series forecasting. We'll use state of the art machine learning frameworks like Keras, TensorFlow, DeepLearning4J and Apache SystemML to show how to apply those models on large-scale, GPU packed cloud clusters as well as on small embedded devices like the Raspberry Pi using Keras.js on top of NodeRED/Node.js

About Romeo: Chief Architect IBM Watson IoT, http://romeokienzler.com/, https://twitter.com/RomeoKienzler, https://www.youtube.com/channel/UC_zIqSWu-yQcBAywLtHDAfg

Talk 3: "New Neural Network Training Algorithms" (Bojan Ploj, Colllege of Ptuj, Slovenia) [Technical Skill Level: Advanced]

Abstract: Bojan invented two new methods for NN training beyond backpropagation: (1) Bipropagation, (2) Border Pairs Method.

About Bojan:College of Ptuj (Slovenia), https://www.linkedin.com/in/bojan-ploj-0a0312131/, https://www.researchgate.net/profile/Bojan_Ploj/publications

Talk 4: "NLP for Swiss German" (Noëmi Aepli, University Zurich & Nora Hollenstein, IBM Research) [Technical Skill Level: All]

Abstract: Natural Language Processing is challenging for any language, yet for dialects there are even more aspects to consider. This talk shall give an introduction to the challenges of developing NLP methods for Swiss German dialects, highlight the differences to Standard German and provide an overview of the research that has been done in this area in recent years. For this purpose, we will present our own contributions including the creation of a Swiss German corpus, part-of-speech tagging, dialect identification, dependency parsing and some observations regarding the phonetical aspects.

About Noëmi: Currently finishing her Computational Linguistics studies at the University of Zurich, developing a parser for Swiss German within the scope of her Master’s thesis. As CorpusLab assistant (@ URPP Language and Space at UZH) she has been involved in Swiss German NLP projects in recent years.

About Nora: Studied Computational Linguistics at the University of Zurich and obtained a M.Sc. in Artificial Intelligence from the University of Edinburgh. After graduating she worked as a technical consultant for Watson projects at IBM before starting her PhD at IBM Research.

Talk 5: "How AI and NLP are helping to understand Swiss German Dialect" (Jürg Schleier, Spitch AG) [Technical Skill Level: All]

About Juerg: Country Manager Spitch AG

Abstract: We all want computers which understands us (the human being) in a natural way, followed by doing the right calculations and conclusions and by taking the right actions or presenting the results in the appropriate way. The IT industry has made enormous progress in this area in the last few years. Artificial Intelligence (AI), Machine Learning (ML) and Natural Language Processing (NLP) are the underlying technologies for these developments. And AI, ML and NLP are the modern buzz words in the IT industry.

But what does these new technologies bring to the business customer and the users? Basically, nothing! Modern Technology "can", but does not need to be a "enabler". And there is still the old rule "Garbage in = garbage out". The key question still remains: can the new technology or solution help me to make something better, faster or cheaper or not?

Spitch is a Swiss based provider of biometric voice- and speech-recognition solutions, which also include the understanding of "Schwizzerdütsch" with an accuracy up to 95%*. We are using AI, ML, and "neural networks" for our solutions. We are offering a great state-of-the-art products – but this only makes sense, if we are able to provide business benefits for our customers. A good example is the speech recognition in the new Mobile Preview App from SBB. Although SBB was already interested in our technology, but we had to prove that we can recognize 18 '000 station names, spoken in 'Schwizzerdütsch' with a precision of more than 90% before we received the order.

We will present how we are using AI, ML and NLP for speech-recognition and we will show a live customer demo how we are generating high-German subtitles out of the SRF Meteo Weather forecast video spoken in Swiss German dialect.