Sooner or later you will probably use python in one of your projects. Either for data science or scripting.
Python is a very easy language to learn. It is very versatile, and non prescriptive. This is its strength, but unfortunately makes it incredibly easy to fall into pitfalls of writing code and structuring projects in a way that is both hard to read, maintain, and test.
As a C# developer it is also very tempting to write code in a C# style, not using all the goodness python has to offer, and writing code that is less performant and uses more resources than good python code.
This session is a journey through things I have learned over the last few years, writing production code in python, so that you don’t have to re-live my mistakes.
Tess is a developer/data scientist working at Microsoft. Over the past 20 years she has changed the way we do .net debugging, developed a large number of mobile apps. As of a couple of years ago she moved into the world of data science and machine learning working with a lot of the largest companies in Europe and beyond on really tough ML problems.
She has has spoken at lots and lots of conferences around the world on a wide variety of topics including deep .net debugging, UX, web development and Machine Learning. You can also find her on twitter at @TessFerrandez
