/Nittany-AI-Rapid-Prototyping-Code

Nittany AI Rapid Prototyping & Deployment

Primary LanguagePythonMIT LicenseMIT

Nittany-AI-Rapid-Prototyping-Code

Nittany AI Rapid Prototyping & Deployment Code is just a starting point for your project. You don't have to use this specific stack, however the benefits of this stack is using python libraries like for tensorflow, sci-kit learn, pandas, numpy, then getting those technologies deployed to the cloud as soon as possible,

Currently this Prototype is missing a mobile application stack in place of Next.JS as alternative.

Prerequisites

  • Install Node
  • Install Python
  • Install Git
  • Create a Google account.
  • Create a Github account.
  • Create a Vercel account to Deploy Next.JS apps
  • Create a Supabase account for database.
  • Install VScode
  • Add python app on VScode
  • Add indent-rainbow on VScode

The Stack

Next.JS -> Vercel Flask App -> Google Cloud -> Supabase (PostgresSQL)

This stack doesn't cover database migration, & updating data in a database. Well for prototyping

Flask App + Python Machine Learning Code or Models

Next.JS

What you learn NextJS tutorial is best thing over to fully leverage this front-end, its also used in industry.

  • Javascript
  • React
  • Web Development concepts

Next.JS is just a React Framework

it just has set of rules to build these things behind a web application

  • User Interface
  • Routing
  • Data Fetching
  • Rendering
  • Integrations
  • Infrastructure
  • Performance
  • Scalability
  • Developer Experience