Tips, Expertise, Articles and Advice from the Pro's for Your Website or Blog to Succeed
AI has become an essential part of our daily lives thanks to its many advantages in a wide range of different circumstances and use cases and how simple and easy it has made things for us to do tasks.
AI has come a long way in the last several years, allowing organizations to thrive and reach their full potential. However, it wouldn't have made these AI advancements if not for the fundamental changes in programming languages.
Before we go ahead with the topic, the readers must have some prior knowledge about web development and Middleware. As observed by its name, Web development is a field of computer science. The developers are responsible for developing websites, whether they are for the internet, intranet, single-page website, blog sites, or complete social media platforms. Middleware acts as a glow-in as it provides the path between the front end and back end of a computer or android based application. The main focus of Middleware is to provide those services which are out of reach from the operating system. This can be demonstrated from a simple example that Middleware is such an architect that is not available on windows or an android based devices. Still, the developer needs that specific part to complete their development, so Middleware comes into play and provides something to them. It acts as an unsung hero in web development.
In web development, Middleware lies between the applications and the operating system. As to the previous discussion, it becomes very obvious that the role of Middleware is very important in web development. While it only acts as a hidden layer, which means the user and even the developer can't see it, if we remove this hidden layer, the user will not be able to run the application. The developer will be unable to develop something like that. Middleware provides communication between the inputs and outputs while the developer can work on developing the website. For a better understanding, below is a figure which can help to improve the concept.
Machine learning (ML) has been developed and growing fast. It also depends on an expert in ML to develop the ML model, i.e. pre-processing, building model, feature engineering, tuning of hyper-parameters, etc. Data scientists have many demanding responsibilities, and challenges. These challenges include the selection of the best algorithm, modification of this algorithm over many iterations, and identification and tuning of the hyper-parameters many times. Despite going through difficult processes, it is worth noting to watch the ML model beat expected accuracy. There is the myth that the developers love to overdo the coding. Many steps that are performed by data scientists are repeatable and time-consuming which makes these steps ideal candidates for automation [1].
Figure 1
Open-source technology refers to a certain type of technology or software which is distributed among the masses with its source code, enabling programmers to change the behavior of an application or program. If a programmer has access to the source code of particular software, he can amend, examine, and made changes to that software by upgrading it with new features or fixing a broken part to increase its efficiency.
The idea of open-source technologies emerged in 1983 when Richard Stallman, a programmer and a researcher at MIT, floated the idea that technology should be open-source. He wanted more freedom for programmers, as he believed that programmers can create better versions of the software and bring revolutionary changes to the technology if they are provided with the source code. This idea led to the creation of the Open Source Initiative, or OSI, in 1998 (Adey, 2021).