All hands-on meetups around hacking traditional machine learning down to creating some intelligent agents and self-driving models.
Who should join: We are open to anybody who is interested in Machine Learning or Data Science from really new, but already passionate up to experienced folks, who would like to play around side projects.
Why members should join: To learn, share, and have fun doing so.
What members can expect: Monthly meeting with knowledge sharing on related topics
🆂🅻🅾🆃 #1: From Research to Production – Our Process at Rasa - Tanja Bunk, Rasa
📑 Using latest research to improve our product is one of the core principles at Rasa. But how do we come from an interesting idea to an actual production ready feature? And what kind of challenges are we facing during this process?
In this talk I will guide you through the different stages an idea needs to go through before it is included in our open-source product. I will show you why feedback is crucial for us and why research features are often first shipped as experimental features.
I will demonstrate all this with the help of a recently released research feature called entity roles/groups.
👩🏻🔬 Tanja studied Software Engineering with a focus on NLP in Potsdam. Her master thesis dealt with the question of how to extract relations between entities from German text. She is one of the early contributors of Flair (https://github.com/flairNLP/flair), which is a state-of-the-art NLP framework that covers a range of common NLP tasks, such as part-of-speech tagging, named entity recognition, or text classification. At Rasa (https://rasa.com/), Tanja currently focuses on natural language understanding. Especially, she is looking into how to leverage the data from knowledge bases in a conversation.
🆂🅻🅾🆃 #2: Transformers in the Wild - Markus Ludwig, AutoScout24
📑 At AutoScout24, we built a search feature that understands natural language and maps the relevant parts of a query to either keywords or filters. This talk shares our learnings from training and deploying a Transformer model that translates natural language to structured queries. We will cover the entire journey from idea to product: from teaching the model new tricks to helping it forget bad habits, and iteratively refining the user experience.
👨🏻🔬 Markus Ludwig is a Senior Data Scientist at AutoScout24 where he builds and deploys machine learning systems that power search and discovery. Before that he worked as a researcher, lecturer and consultant. Markus holds a Ph.D. in Computational Finance from the University of Zurich, Switzerland.
📌As always, we are super happy to have you with a lightning talk on your small or big successes, open source projects or just something amazing you would like to share.
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