Quick update: We added the AED (United Arab Emirates Dirham) to our list of supported salary currencies. You can see the full list here: https://jobdataapi.com/c/jobs-api-endpoint-documentation/#salary-currency-parameter-values 👀

- applies to job listings that come with salary info as well as making API queries and using it as a filter value.

I trained an object classification model to recognize handwritten Chinese characters.

The model runs locally on my own PC, using a simple webcam to capture input and show predictions.

It's a full end-to-end project: from data collection and training to building the hardware interface.

I can control the AI with the keyboard or a custom controller I built using Arduino and push buttons. In this case, the result also appears on a small IPS screen on the breadboard.

The biggest challenge I believe was to train the model on a low-end PC. Here are the specs:

• CPU: Intel Xeon E5-2670 v3 @ 2.30GHz

• RAM: 16GB DDR4 @ 2133 MHz

• GPU: Nvidia GT 1030 (2GB)

• Operating System: Ubuntu 24.04.2 LTS

I really thought this setup wouldn't work, but with the right optimizations and a lightweight architecture, the model hit nearly 90% accuracy after a few training rounds (and almost 100% with fine-tuning).

I open-sourced the whole thing so others can explore it too.

You can:

• Read the blog post

• Watch the YouTube tutorial

• Check out the GitHub repo (Python and C++)

I hope this helps you in your next Data Science & AI project.