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Taming the Beast: SVMs for Big Data Big data has become the lifeblood of modern businesses and research. But with this deluge of information comes a challenge: extracting meaningful insights and making accurate predictions. Enter Support Vector Machines (SVMs), a powerful machine learning algorithm that's proving its mettle in handling even the largest datasets. Traditional SVMs, while effective for smaller datasets, face limitations when dealing with big data due to their computational complexity. Training an SVM on millions or billions of data points can be incredibly time-consuming and resource-intensive. However, recent advancements have paved the way for efficient SVM implementations tailored for the big data landscape. Here's how SVMs are being adapted to handle big data: Distributed Training: Breaking down...