Category: MLOps
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Pandas vs Polars: A Comprehensive Performance Comparison
In the Python data ecosystem, Pandas has long been the de facto library for data manipulation and analysis. However, a relatively new library called Polars is gaining attention for its speed, memory efficiency, and advanced features like lazy evaluation. Polars uses Apache Arrow under the hood and is written in Rust, providing a modern columnar…
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Hugging Face, Model Security, and the Importance of Safe Serialization
In our previous discussion, Saving Your Machine Learning Model: The Good, The Bad, and the Overengineered, we dove into why the way you save your model matters—from convenience to security. Recent news from The Hacker News has further underscored that point. Let’s break down what Hugging Face is, why it’s become a standard hub for…
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Saving Your Machine Learning Model: The Good, The Bad, and the Overengineered
So, you’ve trained a fancy machine-learning model. It took hours, maybe days, and possibly an existential crisis about whether data science was the right career choice. But before you pat yourself on the back and call it a day, you need to save your model—because if it disappears, you might as well have been training…