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106 lessons
Essential Calculus for ML
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Essential Calculus for ML · 106 lessons
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Computing the second derivative
The derivative is a function in its own right: it takes an input and returns the rate of change of there. Like any function, it can be differentiated. Doing so gives a new function, one that measures how fast the rate of change is itself changing rather than how fast is changing.
Definition
The second derivative of is the derivative of :
In Leibniz notation, where , it is written .
The symbol records that the operator has been applied twice. It is a single piece of notation rather than a power, so it does not mean squared.
Computing needs no new rules. The same differentiation rules apply to as applied to .
Procedure
Which rules apply when differentiating is decided by the form of , not by the form of . Differentiating can change that form, so we read the structure of before differentiating it, exactly as we would for any other function.
Compute for .
Solution
We differentiate to obtain . The expression is a product of two factors, so we name them:
Each factor differentiates on its own: the power rule gives , and . Assembling with the product rule,
We simplify . Both terms carry a factor of , so we factor it out:
Written this way, the structure of is visible. It is again a product, but not the product we began with: its first factor is , where the first factor of was .
We differentiate to obtain . Its structure requires the product rule again, now with the factors
giving and . Assembling with the product rule again,
Practice questions
6 questions
Compute for .
Select the correct answer:
+ 5 more questions
Higher-order derivatives of polynomials
The second derivative is not the end of the process. Differentiating gives the third derivative , that function can be differentiated in turn to give a fourth, and so on for as far as we choose to go.
Definition
The order of a derivative is the number of times has been differentiated. Beyond the third, prime marks become impractical to count, so the derivative of order is written .
In Leibniz notation it is written .
For a polynomial, we can find the order at which the derivatives vanish, and the degree of every derivative below it, without computing them. The power rule lowers each exponent by one, so the highest power falls by one at every differentiation. Once the degree reaches the derivative is a non-zero constant, and differentiating a constant gives , so every derivative beyond that order is .
Theorem
If is a polynomial of degree , then is a non-zero constant and
Below that order, has degree .
Only the leading term of the polynomial matters. Lower-degree terms reach at earlier orders of differentiation, so they are never the last to vanish.
Gotcha
The brackets are part of the notation. is the third derivative, whereas means cubed.
Find for , and state the smallest order at which the derivatives become .
Solution
We differentiate four times, applying the power rule to each term:
| Derivative | Expression | Degree |
|---|---|---|
So , and the degree falls by one at each order, as the power rule requires.
The order at which the derivatives vanish follows from the degree alone. The polynomial has degree , so the derivative of order has degree :
a non-zero constant. Differentiating it gives , and every derivative beyond the sixth is as well. The smallest such order is , which the degree tells us directly, without computing the table above.
Practice questions
4 questions
For , find .
Select the correct answer:
+ 3 more questions