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Optical Character Recognition (OCR) and Machine Learning with Ahmad Anis - ML 086

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Manage episode 340629696 series 2977446
Content provided by Charles M Wood. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Charles M Wood or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
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
Links
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
  continue reading

172 episoade

Artwork
iconDistribuie
 
Manage episode 340629696 series 2977446
Content provided by Charles M Wood. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Charles M Wood or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
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
Links
Advertising Inquiries: https://redcircle.com/brands
Privacy & Opt-Out: https://redcircle.com/privacy
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
  continue reading

172 episoade

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