Big O notation - Data Structures & Algorithms Tutorial #2 | Measuring time complexity

Big O notation is the way to measure how software program's running time or space requirements grow as the input size grows. We can't measure this using absolute terms such as time in seconds because different computers have different hardware hence we need a mathematical way to measure time complexity of a program and Big O is that mathematical way. The basic idea is to come up with mathematical function for a running time and consider only fastest growing term and discard other terms as well as constants. Big O is used to measure space complexity as well, You will know how to find the time and space complexity of algorithms.

Clarification: At 5:05, the code should be print(str(numbers[i]) + " is a duplicate"), to concatenate integer with string you need to convert to string or use format string.

#bigo #bigonotation #timecomplexity #spacecomplexity #datastructures #algorithms #python

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[mohitkumargautam]

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[Niko-zlhn]

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[dewanmasumanazneen]

learnt so much more in a 12 min video than my 6 months semester at university...Thank you sir.

[vikasmanav]

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[minhazulislam]

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[generallifing]

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[ritammondal]

Maine 20 se 30 video dekha hay time complexity ke upar par itna simply or example ke sath koy nehi

[akmzahidulislam]

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[talkingexpi]

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[vijitpugalia]

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[Orgwell]

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[_Ayush_Tiwari_]

after watching a lot of videos related to DS, I got this and now I can say that this is the best till you

[gappogappo]

9:46 It took me a while to wrap my head around how exactly he derived the order to be O(log n).

Consider the example he provided: an array of eight digits with the 7th digit being our target value. Using binary search, this example is actually a worst case scenario. Why? Well because we had to go all the way to the 3rd iteration, where we are at an array size of n/(2^3). Basically, since n=8 in this example, we have 8/(2^3) = 8/8 = 1. So we see that the worst case scenario is when n/(2^k) = 1.


Each iteration is cutting the array size in half. The worst case scenario is where we keep having to cut the array size down until it goes from being length n (originally) all the way to 1.

[অর্ণবচ্যাটার্জী-ধ১খ]

i am teaching coding to myself, and soon realise that without knowledge of algo and datastructure its DOA...read many books, understood the basics...but this video is byfar the BEST explanation i have come across...only possible if the tutor understands it well rather than copying from any text book..thank you

[apoorvshrivastava]

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[kzr_]

Your explanations are so simple and interesting, thanks for this !

[mansijain]

Hey! Your explanation was great! But can you provide more examples of how to calculate the time complexities and the increasing order of time complexities?

[braveheartcreations]

I just learn this on my 27th age! What is log what is log2.. haha.. I was sleeping on my maths classes :D What is the main comedy in this?? I have a post-graduation in computer science !!!! :D :D :D