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

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