Optical character recognition, or OCR for short, is used to describe algorithms and techniques (both electronic and mechanical) to convert images of text to machine-encoded text.  Today on the show, Ahmad Anis shares how he applies Machine Learning to OCR for small hardware applications, for example, blurring a face in a video in real time or on a stream to safeguard privacy using AI.  The panel also discusses various strategies related to learning and soft skills needed for success within the industry.

In this episode…
* Optical character recognition (OCR) defined * Multiprocessing vs. multithreading * I/O bound tasks vs. CPU tasks * How to handle a retry in Python * Strategies for employing on small hardware * Template matching and preprocessing * Gray scaling integrations * How to learn and get started within the industry * Reducing the scope and industry soft skills

Sponsors* Top End Devs * Coaching | Top End Devs

Links* LinkedIn: Ahmad Anis * Twitter: @AhmadMustafaAn1