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Real-Time Object Detection: A Deep Learning Project Outline

Real-Time Object Detection: A Deep Learning Project Outline

One of the goals I have this year is to build a Deep Learning (DL) web application and build an accompanying tutorial series to teach others! To start that journey, I have figured out my tech stack that I will be using and settled on the following:

  • Go -> server-side code (looking to use Echo framework)
  • TailwindCSS -> Front-End UI of the Web App (looking to use this starter template with one of these components)
  • Python -> I mean is there really any other coding language to write DL code these days?!
  • Heroku -> hosting of web server API (in this case Go)
  • Netlify -> host static files (CSS, JS, HTML, etcโ€ฆ)
  • Github -> host code

The DL application will not be anything fancy but will detect hand-written digits (in real-time) to actual numbers. I will be using the classic MNIST Dataset for training data, see more here on the dataset.

Picture from Towards Data Science here and also here

I am really excited about this project because I will be learning new languages and frameworks to build an application utilizing DL. Being comfortable with Python, but not Tailwind CSS, Go, or DL, Iโ€™m looking forward to updating my skill set as a programmer AND have fun while doing it! So as I learn new things about each of the above, Iโ€™ll blog about those as well and teach you how to do it!

I have posted on my Twitter about the process of learning Go and my other thoughts on the language as well. See more below and expand the thread๐Ÿ‘‡๐Ÿพ

If you are having a hard time seeing the thread, check out this compiled version here ๐Ÿ˜ƒ. Starting next week, I will create my first blog about DL.

Until that time, โœŒ๐Ÿพ

P.S. To get a more real-time update of my progress with my various projects including this one ๐Ÿ‘†๐Ÿพ follow me on Twitter ๐Ÿฆ!

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