Quinn Tufono
Software, AI, websites, and anything data analysis related.
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Botanical textures — AI-generated concept study
Original speculative portfolio study exploring six tactile botanical subjects: leaf veins, citrus peel, wood grain, petals, amber resin and sage leaves. Created with AI image generation and visually reviewed for a cohesive editorial direction. This is a concept contact sheet, not a photography shoot, commissioned client result, or evidence of ingredient identity.
Approach: agree the ingredient list, crops and intended uses; establish one visual direction; create and review individual images; deliver organized web-ready files with clear provenance.
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Log event report — synthetic portfolio demonstration. A three-event log was checked for the literal text ERROR. The report identifies line 2 without inventing a root cause or altering the log. Line references make each finding traceable. Executed locally with Python. AI-assisted preparation; no client project or earnings claimed.
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JSON to CSV conversion — synthetic portfolio demonstration. Two order objects were exported into three explicitly selected columns with zero missing selected fields. Field order is controlled and the source is preserved. Nested values require agreed serialization rules. Executed locally with Python. AI-assisted preparation; no client project or earnings claimed.
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CSV reconciliation — synthetic portfolio demonstration. Two three-row inventory exports were compared by SKU: two matched records, one quantity change from 4 to 6, one removed record and one added record. Blank or duplicate keys are rejected rather than guessed. Executed locally with Python. AI-assisted preparation; no client project or earnings claimed.
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