List of videos

Gait phase recognition using machine learning algorithm with IMU sensors by Binbin Su
Gait phase recognition using machine learning algorithm with IMU sensors Gait phase recognition is of great importance to develop accurate timing feedback for exoskeleton control. A powered exoskeleton can provide proper assistance to the subject if the current gait phase can be identified accurately. Machine learning classifiers were built in python to distinguish 4 gait phases in a gait cycle.
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A developer amongst (data) journalists by Eléonore Mayola
A developer amongst (data) journalists I've been working as a developer with data journalists for a year now and I contribute to teaching Python to journalists, building a pipeline of data stories, analysing climate data... In my talk I'll share my experience at jplusplus and discuss technologies and processes transferable between software development and data journalism.
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Binding the Sea by Åke Forslund
Binding the Sea Python is good but sometimes C is better. ctypes offers a strange but not too difficult bridge.
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Build your own event loop by Pradip Caulagi
Build your own event loop Want to handle a lot of traffic with the same hardware? This talk will show you asyncio examples. Together we will build a loop where you’ll be buying the latest accessories for your new horse! We will also explore this in other event loop such as Trio and Curio.
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Closing keynote by Adam Tornhill
A Crystal Ball To Prioritize Technical Debt Most organizations find it hard to prioritize and repay their technical debt. The main reason is due to the scale of modern systems with million lines of code and multiple development teams; No one has a holistic overview. So what if we could mine the collective intelligence of all contributing programmers and start to make decisions based on data from how the organization actually works with the code? This session introduces one such approach with the potential to change how we view software systems. In this session you'll get an introduction to techniques that help us uncover both problematic code as well as the social dimension of the teams that build your software. The techniques are based on software evolution and findings from various fields within psychology. This combination lets you prioritize the parts of your system that benefit the most from improvements, detect organizational issues and make practical decisions guided by data. Each point is illustrated with a case study from a real-world codebase. This is a new perspective on software development that will change how you work with code.
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Keynote: The Ubiquity of Operationalizing Python Models
As we progress further into the Information Age, the number of factors involved in making important business decisions increases exponentially. We will discuss the benefits of operationalizing Python models to better inform the increasingly complicated choices that need to be made in an increasingly complicated world, as well as highlight examples that showcase the ubiquity of this approach. Speaker: Shammamah Hossain. Since June 2018, Shammamah has been working at Plotly as the main engineer for the Dash DAQ and Dash Bio libraries.
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