The Django framework saves time and effort and helps to create apps and REST APIs with maintainable code. This post gives some practical examples of what to do and what not to do when you code in Python using Django. In this post, I’ll explain why good code structure and
Developers often decide whether to build monolithic or microservices architectures based on personal preference. This article tells you how to design the best platform for your client by considering both methods.
Monolithic all-connected platforms might serve a startup’s needs, but they often have problems with scaling to support growth. Architectures built with modular microservices work well for bigger enterprises, but they might be overengineered to require more resources than a startup can spare. This article explains how to incorporate both these build approaches to design a functional strategy from the start that evolves to fit each point in a project’s lifecycle.
A bird-eye view of the machine learning landscape.
The main goal of this article is to cover the most important concepts of machine learning, and lay-out the landscape. The reader will have the vision to understand what kind of solution matches a specific kind of problem, and should be able to find more specific knowledge after diving into a real-life project.
I’ll start with a 60 years old definition, but still valid today:
The name is pretty self-explanatory, and the definition reinforces the same concept.