Know Your Tech

  When you have defined the user stories (requirements) for a new system, the next step is to design the system architecture. There are two main parts to this: 1. Logical Architecture :  This is a high-level view of the system, focusing on the different components or building blocks needed to meet the requirements. It's like a blueprint for the system, showing how the different pieces should work together. ⠀For example, if you're building a system to report bugs, the logical components could be: * Ticket Creation * Ticket Assignment * Notifications (to the requester and resolver) * Communication (adding notes to the ticket) * Ticket Closure ⠀The logical architecture doesn't go into the technical details of how each component will be built. It just maps out what components are needed and how they should interact. 2. Physical Architecture:  This is the more technical view of the system, specifying the actual technologies and infrastructure that will be used to build the com...

A few weeks ago, we discussed   representation learning , which allows an algorithm to automatically discover and learn the most useful features from the data itself (unlike classic machine learning that relies on human-defined features). However, representation learning has a limitation when it comes to intricate problems like voice or image recognition, where it becomes challenging to create a representation due to complexities. For instance, in speech recognition, accents pose a difficulty in representing them as a mere set of features. This is where deep learning steps in to solve this problem. Deep learning expresses the representation in terms of other simpler representations. For example, if we need to identify whether an image depicts a car or an animal, the first input to the model can be just the colors. These colors then serve as input to another representation of edges, which further feeds into contours, and so on, until after multiple layers, we can understand the type...