Decoding Supervised Learning: Decision Trees, Random Forests, and SVMs In the ever-evolving landscape of data science, choosing the right algorithm is paramount for building effective predictive models. Supervised learning, where algorithms learn from labeled data, forms the backbone of many such models. Among the plethora of available algorithms, Decision Trees, Random Forests, and Support Vector
