PYCON (Python Conference) is an annual convention for the discussion and promotion of the Python programming language. It originated in the USA but is also held in Sweden. As Europe’s “Silicon Valley”, Sweden has many active Python developers. The content of the conference covers most of the hotspot aspects, from data analysis, Python frameworks to data ethics. In this text, I will sum up my thoughts about two of the topics: Data Classes and Machine Learning.
Data Classes, in Python 3.6 and beyond by Alexander Hultnér
In this talk, Alexander Hultnér showed how to use the power of data classes to make our codebases cleaner and leaner in a pythonic way. An important task of a Python data analyst in their work life is to extract, process, define, clear, arrange, and then understand data to develop intelligent algorithms. Data is the key and the understanding of data is crucial. With data classes, we do not have to write boilerplate code to get proper initialization, representation, and comparisons for any object which make our life easier.
Mantra – A Deep Learning Development Kit by Ross Taylor
Mantra is a new open-source Python library for managing deep learning projects. In this talk, Ross Taylor demonstrated how to use Mantra for deep learning projects, and how it can help machine learning engineers to quickly iterate and move from idea to production. Python serves us a huge, battle-tested and ready-to-use libraries which can do all the heavy lifting for us. Right now, we have different packages for training or evaluating a model by using existing methods. All we need to do is to write the code that would glue everything together. As simple as that.
Images from PYCON 2018
Consultant at Go See Talents