This tutorial will cover the basics of Rasa, an open source library for building chatbots, including how words are translated into machine learning features and how the next conversation turn is picked. Then we'll quickly build a simple bot together and answer audience questions. Dr. Rachael Tatman is a senior developer advocate at Rasa, where she helps developers use open source software to build great conversational AI projects. Before that she was at Kaggle (part of Google) and doing a PhD in Linguistics. If you hear a dog in the background, his name is Benson. PUBLICATION PERMISSIONS:
PyData Organizers provided Coding Tech with the permission to republish PyData talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/channel/UCOjD18EJYcsBog4IozkF_7w https://www.youtube.com/watch?v=VpvmLxO3Ys0

Utilizing machine learning models to improve search has been an immensely active area for several years now. Some promises were kept, many others were broken. With the rise of Transformer models like BERT we seem to finally be entering a chapter, where models not only perform well in the research lab but actually make their way into the production stack. Now that almost every English Google search query is powered by a Transformer [1], it is clear that these models improve the search experience, and can do so at scale. As Transformers only rely on text, the transition from web search to a custom enterprise search seems more tempting than ever. In this talk, we will dive into some of the most promising methods and show how to … … improve document retrieval via dense passage retrieval … return more granular search results by showing direct answers to user’s questions
… scale those pipelines via DAGs and Approx. Nearest Neighbour search (ANN) for production workloads
… avoid common pitfalls when moving to production All methods will be illustrated with code examples based on the open-source framework Haystack [2] so that participants can easily reproduce them at home and let the transformers into their production stack – one by one and carefully selected! PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=0FHdB00Mx7c https://www.youtube.com/watch?v=uQCpMISt9hs

Programming languages are places. The idea of abandoning the convenience and familiarity of your primary coding language might seem anything from tedious and inconvenient to scary and stressful. But, switching to an alternative other than your primary development language — especially when such a challenge is not a requirement — can be both fun and productive. You will likely grow your abilities as a developer and gain new perspective that is currently beyond your reach.
Let's push out of our comfort zone together to leave Python and voyage to a different language! We will go into details about why and how we can do that, along with some possible destinations. Upon our return, we will see — and appreciate — Python in a different light. Plus, we can use the justifications for our departure to entice and welcome folks from other language communities to visit us in the land of the snake. Slides: https://pirsquared.org/talks/pycon_tw/ PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=iO633Om2QmU https://www.youtube.com/watch?v=O2ArH_MoeKQ