The learning algorithms mostly use some mechanisms or assumptions by either putting some restrictions on the space of hypotheses or can be said as the underlying model space. This mechanism is known as the Inductive Bias or Learning Bias.

This mechanism encourages the learning algorithms to prioritise solutions with specific properties. In simple words, learning bias or inductive bias is a set of implicit or explicit assumptions made by the machine learning algorithms to generalise a set of training data.

Here, we have compiled a list of five interesting inductive biases, in no particular order, which are used in deep learning.

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