C. It's honestly up to the user, upload so others can use it or make it so its copyrighted and make some cash :P
The statements that correctly describe the time complexity of data structures with N data are:
- The average time complexity of the data lookup in a hash table is O(N).
- The average time complexity of inserting data into a heap is O(logN)
<h3>What is time complexity of data structures?</h3>
Time Complexity of an algorithm is known to be the depiction of the amount of time needed by the algorithm to carry out to completion.
Note that The statements that correctly describe the time complexity of data structures with N data are:
- The average time complexity of the data lookup in a hash table is O(N).
- The average time complexity of inserting data into a heap is O(logN)
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def dx(fn, x, delta=0.001):
return (fn(x+delta) - fn(x))/delta
def solve(fn, value, x=0.5, maxtries=1000, maxerr=0.00001):
for tries in xrange(maxtries):
err = fn(x) - value
if abs(err) < maxerr:
return x
slope = dx(fn, x)
x -= err/slope
raise ValueError('no solution found')
<span>There are some network modeling tools that can scan the existing network.</span>
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