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December 19, 2024

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Convergence: What is convergence and non-convergence of an algorithm
Content

1.
What is convergence in mathematics
2.
Convergence in Machine Learning
3.
Types of Convergence in Machine Learning
4.
How to understand that convergence has been achieved
5.
Can a model "not converge"
6.
What does slow convergence mean?
7.
How to increase the speed of convergence
8.
Brief conclusions
Anna Mavrina
Anna Mavrina
Skillfactory author with engineering education

Machine learning algorithms and models are evaluated by various luxembourg telegram data parameters: they determine how quickly and accurately the model works. One of these parameters is convergence of the algorithm. Convergence shows how quickly the model reaches its “optimum” — the point beyond which it makes fewer mistakes and makes more accurate predictions.

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Let's take a closer look. We'll explain in simple terms what convergence is, together with Alexander Nemaltsev, head of the machine learning group at VK.

What is convergence in mathematics
By definition, convergence is a property that means that something has a finite limit. For example:

finite sum of the members of an infinite series of numbers;
final value of the integral;