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Deploying Intelligence Across the Cloudscape: Azure vs Google Cloud for ML Projects
In the symphony of data-driven impact, deploying machine learning isn’t a solo performance. It involves orchestrating diverse components—from fetching data to packaging intelligence, deploying resilient…
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Pivot with Purpose: A Systems Design Perspective
In systems design, movement isn’t always momentum. Sometimes it’s recalibration. When structures feel off-kilter or feedback loops stall, the answer isn’t always to push through—it’s…
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Pickle vs. Joblib: Choosing the Right Travel Companion for Your ML Models
Whether you’re deploying your first machine learning model or orchestrating a multi-layered pipeline, serialization—saving models to disk and loading them later—is a critical part of…
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Why Questions Matter—and Why Framing Matters Even More
In software engineering, AI development, and strategic planning, asking the right question is not a soft skill – it’s a tool that guides clarity, collaboration,…
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Innovation Amnesia & the New Baseline
In the age of accelerating automation, intelligent pipelines, and generative breakthroughs, it’s tempting to believe that progress is measured only in throughput, precision, and code…
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Why Python Is the Go-To Language for Machine Learning
In the sprawling landscape of machine learning, one programming language quietly dominates the terrain: Python. But this isn’t just a matter of popularity-it’s a matter…
Blog
A collection of thoughts, experiments, and occasional rants. I write about tech – sometimes deep dives, sometimes half-baked ideas – and sprinkle in reflections on life, work, and the curious patterns that connect them. Expect a mix of machine learning, digital philosophy, and the kind of randomness that only makes sense in hindsight. No promises, just perspectives.
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