Learn how to implement coding best practices to avoid tech debts
Many people approaching machine learning don’t have a strong background in computer engineering, and when they need to work on a real product their code can be messy and difficult to manage. This is why I always strongly recommend learning to use coding best practices which will enable you to work smoothly within a team and level up the project you’re working on. Today I want to talk about Python inheritance and show some simple examples of how to use it within the field of Machine Learning.
In software development and other information technology fields, technical debt (also known as design debt or code debt) is the implied cost of future reworking because a solution prioritizes expedience over long-term design.
If you are interested in learning more about design patterns you might be interested in some of my previous articles.
Inheritance it’s not just a Python concept but a general concept in Object Oriented Programming. So in this tutorial, we have to deal with classes and objects which is a programming paradigm not very used in Python with respect to other languages like Java.
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