While OO and FP are orthogonal, they are not mutually exclusive. That a good functional program can (and should) be object oriented. And that a good object oriented program can (and should) be functional.
Over the years, we’ve all heard some skepticism around using functional programming on a real life project. In our view, most of this skepticism stems from the perception that functional programming is inaccessible, overly academic, or not terribly useful.
Debuggable code is code that doesn’t outsmart you. Some code is a little to harder to debug than others: code with hidden behaviour, poor error handling, ambiguity, too little or too much structure, or code that’s in the middle of being changed. On a large enough project, you’ll eventually bump into code that you don’t understand.
The amounts of data processed by applications are constantly growing. With this growth, scaling storage becomes more challenging. Every database system has its own tradeoffs. Understanding them is crucial, as it helps in selecting the right one from so many available choices.
Data scientists spend a large amount of their time cleaning datasets and getting them down to a form with which they can work. In fact, a lot of data scientists argue that the initial steps of obtaining and cleaning data constitute 80% of the job.
Yet another type of surreptitious data collection by third-party scripts: the exfiltration of personal identifiers from websites through “login with Facebook” and other such social login APIs.
Object detection is a domain that has benefited immensely from the recent developments in deep learning. Recent years have seen people develop many algorithms for object detection, some of which include YOLO, SSD, Mask RCNN and RetinaNet.