From the course: Complete Guide to Calculus Foundations for Data Science
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Newton's method
From the course: Complete Guide to Calculus Foundations for Data Science
Newton's method
- [Instructor] Last up, let's explore Newton's method. You'll see how you can use this method with derivatives to approximate solutions to functions. Let's get started. Newton's method is helpful to use when you have an equation you wish to solve for zero. This is helpful when there's no way to do so algebraically. You can use it to estimate equations like sine of X equals X or F of X equals zero equals X to the fifth, plus eight multiplied by X to the fourth, plus four, multiplied by X cubed, minus two multiplied by X minus seven. It's also great to estimates gray roots such as the square root of 38. Newton's method provides a way to approximate the solution for function F of X, where F of X equals zero. The initial estimate is referred to as X naught, and the following estimates are referred to as X one, X two, and so on. For as many iterations as you perform, Newton's method is an iterative process, meaning you can repeat it as many times as needed. Let's take a look at the formula…
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