Uploaded December 2017 | Updated September 2026, 1 week ago
In this talk we will cover the ways in which we can use Pythons packaging tools and best practices in order to make sharing our machine learning solutions easier.
We will cover the basics concepts and tools for Python packaging. Then we will introduce a few suggested schemes for how to package a machine learning project, followed by some tips and best practices.
We will wrap up with a few additional concerns related to creating quality projects and packages.
A good precursor to the talk is a blog that I wrote as a companion to this talk. It can be found at blog.stevencutting.com.
In this talk we will cover the ways in which we can use Pythons packaging tools and best practices in order to make sharing our machine learning solutions easier.
We will cover the basics concepts and tools for Python packaging. Then we will introduce a few suggested schemes for how to package a machine learning project, followed by some tips and best practices.
We will wrap up with a few additional concerns related to creating quality projects and packages.
A good precursor to the talk is a blog that I wrote as a companion to this talk. It can be found at blog.stevencutting.com.
