How to choose the right ML model for a problem?
With so many algorithms available, how do you decide which one to use? Is it better to start simple or go straight to advanced models?
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Choosing the right machine learning model is not about selecting the most complex algorithm, but about matching the solution to the problem. Starting with simple models often leads to faster and more reliable results. Many teams encounter common data science problems when they overcomplicate solutions instead of focusing on practical performance and clear business value.