Parameters
In the context of data science and artificial intelligence, parameters refer to the values that are used to define a model or algorithm. These values are set by the data scientist or machine learning engineer and are used to optimize the performance of the model. Parameters can be adjusted to improve the accuracy of the model or to reduce overfitting. In machine learning, parameters are often learned through an iterative process, such as gradient descent, where the algorithm adjusts the parameters to minimize the error between the predicted output and the actual output. The choice of parameters can have a significant impact on the performance of the model, and selecting the optimal values can require extensive experimentation and tuning.
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