Posts
All the articles I've posted.
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Image Classification Training Pipeline — An 11-Step Checklist
I abstracted the training flow I learned yesterday through the NDT hands-on exercise into a step-by-step checklist applicable to any image classification problem. Along with small questions like why normalization is needed.
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NDT Defect Classification Hands-on — From PyTorch + ResNet18 Transfer Learning to Grad-CAM
An opportunity came up to put my embedded object recognition experience to use, so I picked up NDT (non-destructive testing) again. A hands-on record of training a 6-class defect classifier on the NEU Steel Defect dataset using transfer learning, and visualizing the model's decision basis with Grad-CAM.
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Claude Vision — How Do You Send Images In, and Which Model Should Receive Them
I tried both ways of sending images — base64 encoding and URL — and found them accurate but more token-costly, hit limits with small text and complex shapes, and got a sense of when to move up to a bigger model for tasks that need accuracy.
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Giving LLMs Tools — Claude Tool Use and the Agent Loop
LLMs don't know large-number arithmetic or today's weather. I tried out Tool Use, which patches that weakness with external function calls. Message flow, automatic multi-tool selection, and the agent loop.