Web apps
Verified by Star Health Data Science Team


Our engagement with digital electronics has increased tremendously. It is only anticipated that the aforementioned exchanges would multiply significantly in the upcoming years. Apps serve as the common platform for these interactions between humans and technology.

App- This word doesn’t even need a definition or an introduction. Over the past decade, we have used and interacted with applications more and more frequently. There is an app for anything you can imagine, from ordering a needle to purchasing a vehicle. Even now, you’re probably viewing this piece on an app.

In this blog, we will focus on web apps and the technologies used to design and maintain web apps and their applications.

We may essentially divide the applications into three groups based on the kind of devices they are used on:

1. Native Apps

Native apps are created especially for a mobile device’s operating system (eg.- IOS or Android).

2. Web applications

Web applications are mobile-friendly variations of websites that may be tailored to your own company or cause.

3. Hybrid Applications

Hybrid Applications involve the combinations of two apps. These applications are more platform-flexible.

Web apps are specialised websites that may be used to operate and modify services according to a user, as we have already said.

You may have come across the following instances of web applications in your daily life:

1. One of the commonly used web apps is banking sites.

2. Several subway/train booking networks use web apps to manage reservations and itineraries.

3. Almost every grocery store you visit employs a web application to keep track of its stock and inventory.


Web apps may be requested on browser interfaces and don’t need to be downloaded. In this post, we will emphasize the Streamlit-based web app more.

Streamlit is a Python-based open-source app framework. It enables us to develop web applications for data science and machine learning quickly. Major Python libraries like scikit-learn, Keras, PyTorch, SymPy (latex), NumPy, pandas, and Matplotlib are all compatible with it.

It is used to integrate various Machine learning and AI functionalities with an Attractive GUI and makes it accessible to anyone with no coding or ML experience.

In any organisation, when we talk about productionizing a model, it is known to everyone that the time between the development to deployment phase is not so quick. And in fact, many of the models will be in the development phase and won’t move to the deployment phase due to various reasons.

By designing a web app for multiple use cases, we could show a demo to the stakeholders of what are we trying to build and how the outcome would look like. Also, before it gets implemented live, the same web app could be given to the business team to get used to the new change before real-time implementation.

Also, many of the adhoc based use cases can also be deployed by creating a simple web app.


Webapp has many benefits which increase their accessibility. Since you do not have to download a package for installation, the risk and storage space requirement is significantly reduced. This also cuts down on installation and development costs significantly.


To summarise, a web app is a very efficient tool in providing a quick solution to business end users. And with an increase in advanced technologies, we can expect many more such tools to be implemented to meet and fulfil the requirement.

Thanks for giving it a read. Be tuned for some other exciting and informative blogs.

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