What are numerical methods and how are they used in data science?
An example of an AI chatbot conversation about numerical methods in data science.
What are numerical methods and how are they used in data science?
Numerical methods are techniques used to solve mathematical problems by numerical approximation. In data science, they help in optimization, simulations, and solving equations that arise in data analysis.
Can you give me an example of a numerical method used in data science?
Sure! One common numerical method is gradient descent, which is used for optimizing machine learning models by minimizing the loss function.
How does gradient descent work?
Gradient descent works by iteratively adjusting the parameters of a model in the direction of the steepest decrease of the loss function, using the gradient.
What are some challenges associated with numerical methods?
Challenges include numerical instability, convergence issues, and the need for careful selection of parameters to ensure accurate results.
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