Jan 12 · 3 min read · 📜 Why Training and Deployment Can’t Be Manual In early ML projects, training and deployment are often manual: Run a notebookSave a model fileUpload it to production This approach fails at scale. Problems include: Inconsistent resultsHuman errorNo qu...
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Jan 8 · 12 min read · AI is ingrained in our everyday lives. You have a query? You talk to a chatbot. You want to sort your email inbox? You reach out to an AI assistant. You’re scrolling through a streaming app? AI will recommend what to watch. But beyond this, pretty mu...
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Jan 28, 2025 · 7 min read · Introduction 🤔 "How can you be sure your machine learning model is truly effective? Is it capable of making accurate predictions on data it has never seen before? The answer lies in an essential process known as Model Validation." Model validatio...
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Jan 30, 2024 · 8 min read · Let's examine an Azure Function that takes a string input request and subsequently serves that same data to the web for rendering. Assume the text below is the input: "<img src=x onerror=\"confirm('System Compromised')\">" Without any sanitization b...
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Jan 21, 2024 · 4 min read · Overfitting happens when a model is more complex than it should be and starts to fit the noise in the data (or some degree of that) instead of the underlying pattern. Overfitting leads to poor model performance on new and unseen data. While there is ...
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Jul 4, 2023 · 6 min read · This article shows, how one can return a structured response from an ASP.NET web API in case of errors (exceptions & model validations). One way to do that is by using custom ProblemDetailsFactory. 1. What is ProblemDetailsFactory? ProblemDetailsFact...
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