Apr 12 · 10 min read · Imagine a student who is, in one very specific sense, the best studier in her class. The teacher hands out a practice test before the real one. Our student takes it home and memorises it. Every question. Every answer. Every typo. If you ask her the t...
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Apr 6 · 6 min read · The ML Model's Tightrope Walk: Balancing Bias and Variance for Peak Performance Introduction: The Goldilocks Problem of Machine Learning Welcome, aspiring data scientists and ML enthusiasts! Ever wondered why some machine learning models perform bril...
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Mar 29 · 15 min read · TLDR: 🎯 Accuracy is a lie when classes are imbalanced. Real ML evaluation uses precision (how many positives are actually positive), recall (how many actual positives we caught), F1 (their balance), and AUC-ROC (performance across all thresholds). T...
Join discussionMar 29 · 18 min read · TLDR: 🎯 Accuracy is a lie when classes are imbalanced. Real ML evaluation uses precision (how many positives are actually positive), recall (how many actual positives we caught), F1 (their balance), and AUC-ROC (performance across all thresholds). T...
Join discussionMar 29 · 16 min read · TLDR: 🎯 Accuracy is a lie when classes are imbalanced. Real ML evaluation uses precision (how many positives are actually positive), recall (how many actual positives we caught), F1 (their balance), and AUC-ROC (performance across all thresholds). T...
Join discussionFeb 3 · 34 min read · I once questioned whether I belonged here and proved it to myself. This week, I taught a machine to think. Not in the sentient, Terminator way, but practically and elegantly, that makes you wonder why anyone ever made predictions manually (for all yo...
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Jan 30 · 10 min read · In the rush to adopt AI and automation, many teams implement human-in-the-loop (HITL) frameworks. They believe that involving a person in the process solves the problems with reliability, quality, and trust. But as we’ve learned from real engineering...
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Jan 23 · 19 min read · Every day, we learn something new about generative AI applications – how they behave, where they shine, and where they fall short. As Large Language Models (LLMs) rapidly evolve, one thing becomes increasingly clear: selecting the right model for you...
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Dec 29, 2025 · 6 min read · I used to trust accuracy far more than I should have. The first time I trained a classifier that crossed 95%, I remember the quiet satisfaction. The curve looked clean. The confusion matrix was almost boring. I took a screenshot. Sent it to a friend....
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Nov 26, 2025 · 9 min read · Are Tech Giants Secretly Training AI Models on Your Personal Data? You share photos on Instagram. Send messages on WhatsApp. Upload documents to Google Drive. Post professional updates on LinkedIn. Search for medical symptoms. Voice chat with friends...
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