Model Optimization

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Bias, Variance, and Overfitting Explained, Step by Step cover image

Bias, Variance, and Overfitting Explained, Step by Step

You have likely heard about bias and variance before. They are two fundamental terms in machine learning and often used to explain overfitting and underfitting. If you're working with machine learning methods, it's crucial to understand these concepts well so that you can make optimal decisions in your own projects. In this article, you'll learn everything you need to know about bias, variance, overfitting, and the bias-variance tradeoff.

  • Boris Giba