Built a Machine Learning Pipeline

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DevSecOps Specialist, Xurya Daya Indonesia
Feb 05, 2021
Enhancement completed, than let's see what happen if we implement it into web-based. 
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DevSecOps Specialist, Xurya Daya Indonesia
Jan 25, 2021

Machine Learning Pitfalls (2)

If you ever think about these, then you're not ready to develop machine learning.
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DevSecOps Specialist, Xurya Daya Indonesia
Feb 02, 2021
Well this photo explains everything.
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DevSecOps Specialist, Xurya Daya Indonesia
Dec 07, 2020
Currently I'm developing an Artificial Intelligence or Machine Learning that focuses on Image Processing. It's more like a research and development. After having a discussion with external teams in choosing tools, i decided to train all the datasets in AutoML service from Google Cloud Platform. 

Besides the r&d phase, all implementation that related to the machine learning needed for further like web development, so user able to scan it via web-based i guess. Or even API that connects the machine learning system with a mobile app. Let's settle my goals at first for this development.

Expectation

  • The system able to detect the brand and the type of the bike, the machine learning itself detect a brand of a bike, or even type of the bike (release year too. it'll be awesome if its able. lol). Farther image capture would be recommended for this kind of prediction to ensure it achieves accurate prediction. (example -- left image).

  • The system able to detect the quality of the parts. In this case. close-up photo-angle needed like right side images. It prevents the misleading label-detection. Besides that, it helps the condition of the part are seen enough clearly for the prediction such as the scratches, dents, etc.

  • The system able to differentiate customized and original parts. Since we're going to value every single part of the bikes, original parts that still attached on the bikes will get better values than customized parts (in the market). So that's why it's quite important to be able detect those. 
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Unity Developer, Aurorian Studios
Nov 21, 2020
Throughout 2020, my final year of high school, I was involved in a number of initiatives and projects, from the 2019/20 Open Source Rover challenge, to Microsoft's AI for Good Challenge. A few of these competitions and projects (like the AI for Good or the Australian Space Design Competition) were done through school, while a few were done with my own development team. I was named a "Future Innovator" by the Australian Defence Force due to my accomplishments in 2020 and I wrote this article shortly after:

https://dev.to/gizmotronn/game-engine-future-innovators-award-1hpf
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Data Science Intern, Rebel Foods
Dec 16, 2021
Completed a bunch of awesome projects with Transformers! Learned to play around with BERT, T5, Bart & PyTorch Lightning as well. Here's a sneak peek:

  1. Built a tool to summarize YouTube Videos & Blog Posts. Talk about saving time eh?
  2. Fine-tuned a BERT Model with a custom dataset from a Kaggle Challenge with PyTorch Lightning to classify Multilabel Texts.
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