Python-bloggers

Techtonique web app for data-driven decisions using Mathematics, Statistics, Machine Learning, and Data Visualization

This article was first published on T. Moudiki's Webpage - Python , and kindly contributed to python-bloggers. (You can report issue about the content on this page here)
Want to share your content on python-bloggers? click here.

This week, I released Techtonique web app, a tool designed to help you make informed, data-driven decisions using Mathematics, Statistics, Machine Learning, and Data Visualization. As of September 2024, the tool is in its beta phase (subject to crashes) and will remain completely free to use until December 24, 2024.
After registering, you will receive an email. CHECK THE SPAMS.
A few selected users will be contacted directly for feedback, but you can also send yours.

The tool is built on Techtonique and the powerful Python ecosystem. At the moment, it focuses on small datasets, with a limit of 1MB per input. Both clickable web interfaces and Application Programming Interfaces (APIs, see below) are available.

Currently, the available functionalities include:

As mentioned earlier, this tool includes both clickable web interfaces and Application Programming Interfaces (APIs).
APIs allow you to send requests from your computer to perform specific tasks on given resources. APIs are programming language-agnostic (supporting Python, R, JavaScript, etc.), relatively fast, and require no additional package installation before use. This means you can keep using your preferred programming language or legacy code/tool, as long as it can speak to the internet. What are requests and resources?

In Techtonique/APIs, resources are Statistical/Machine Learning (ML) model predictions or forecasts.
A common type of request might be to obtain sales, weather, or revenue forecasts for the next five weeks. In general, requests for tasks are short, typically involving a verb and a URL path — which leads to a response.

Below is an example. In this case, the resource we want to manage is a list of users.

In Techtonique/APIs, a typical resource endpoint would be /MLmodel. Since the resources are predefined and do not need to be updated (PUT) or deleted (DELETE), every request will be a POST request to a /MLmodel, with additional parameters for the ML model.
After reading this, you can proceed to the /howtoapi page.

To leave a comment for the author, please follow the link and comment on their blog: T. Moudiki's Webpage - Python .

Want to share your content on python-bloggers? click here.
Exit mobile version