server side

Our ML model will be trained locally first. After the local stage, the model will be deployed in the cloud using Flask and Amazon EC2. The data will be stored using MongoDB, and we will use MongoDB Atlas to host it remotely. Below are the reasons why we choose above stacks:

MongoDB and MongoDB Atlas

• Schema-less (Easy to add/remove attributes)
• It is easy to set up and run in Amazon EC2

Flask:

• python library support
• easy and simple to use

Amazon EC2:

• Easy to use/configure
• Secure

Client side

JavaScript will be our main language for front-end. We will use React to build our web interfaces. Material-UI will be used for designing the theme, because it has lots of pre-defined themes. Redis is a great tool for caching due to its in-memory data structure, it can be used to improve user experience. In terms of visualizing data, we use Chart.js. Because it is light weight and easy to learn.

Project management

We use Slack for communication, because it is efficient, light weight and easy to use. GitHub will be used as our primary version control, issue tracking, and roadmapping tool. Because it provides a all-in-one place for code writing and progress tracking.

As our team will be building a web application, HTML5 and CSS3 are one of the standardized combinations to implement the structure and the styling of a webpage. Material-UI comes with all sorts of predesigned web components such as buttons and dropdowns that will save us tons of development time. Since it is a component library designed for React, it suits our needs. However, we do acknowledge that predesigned components may sometimes cause pains especially when it comes to custom styling. To make our life even easier, we also adopted Tailwind CSS. It is a CSS framework providing low-level utility classes that will act as building blocks when we create custom designs.

Backend:

Python is a great industry standard language that can easily handle both machine learning and web development tasks. Our dev team is very familiar with the language and has used it in various web and Machine learning projects. Python has many versatile ML specific libraries that include TensorFlow, Pytorch, Pycaret, and Keras. It also has packages for data manipulations and visualization like Numpy, Pandas, and Matplotlib. Since our software requires machine learning algorithms, big data processing and a backend server, Python seemed like the way to go.

Our team decided to go distributed databases (NoSQL) over a relational database (SQL) because of the NoSQL dynamic schemas for unstructured data. We are using MongoDB as our NoSQL database due to its simplicity, schema less documentation, deep/fast querying ability, user data management, big data, JSON style documents, and great scaling out. We also chose MongoDB due to its horizontal scaling as a NoSQL database.

Since we are using python as our backend programming language, we decided to use Flask as our web framework. Flask is a micro and lightweight web framework that provides the required functionality to efficiently develop our web server. Flask has a great community with many online resources and provides more flexibility in terms of customization when compared to other frameworks like Django. While Django is great for large scale applications, it does not work well with NoSQL databases.

Frontend:

For our front end framework, we decided to go with React due to its component based structures, flexibility, scalability, and high performance. React has a strong community and is trusted by top companies such as Facebook, Netflix, and Paypal. We can also easily transition our react app to a react native or electron app. We will also be using material-ui framework alongside react for that crisp google material design!

Node.js will be used for development purposes for the front end only. Once we deploy for production, the react frontend will be served from the flask web server and will not require Node.js. This separates the frontend and backend during development, making it easier to work with.

Javascript is one of the most widely used languages for front end development and we will be using it alongside React to develop our user interface. Our dev team is familiar with it through previous web projects. Given how popular it is, its community is very active for any problems that come up and is easy to hire for in the future.

Fonts and typography are fun. Material Design is a framework (developed by Google) that basically geeks out on how to assemble your typographical elements together into a design language. If you're into fonts and typography, it's fantastic. It provides a theming engine, reusable components, and can pull different user interfaces together under a common design paradigm. I'd highly recommend looking into Borries Schwesinger's book "The Form Book" if you're going to be working with Material UI or are otherwise new to component design.

https://www.amazon.com/Form-Book-Creating-Printed-Online/dp/0500515085