Dot Product

In linear algebra, the dot product is an operation that takes two vectors of the same dimension and returns a scalar. It is also known as the inner product or scalar product. The dot product is calculated by multiplying the corresponding entries of the two vectors and then summing the products. The dot product has many applications in data science, including in machine learning algorithms such as linear regression and neural networks. In these contexts, the dot product is used to calculate the similarity between two vectors or to project one vector onto another.
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