You are the single greatest python teacher in the world, even Charles Severance can't teach as well as you. I watched so many videos on Big O but this is literally the first time I ever understood it
thankyou so much sir i cant even express how you helped me by uploding this video i request you please complete dsa series thankyou somuch i owe you!!!!keep doing
I have query in Binary search. As you said "if Target is less than the Mid value, then after Mid values of the array have no importance [8:37]". Why we count Mid value here for next loop ? We already know, Mid value is greater than Target value. It should be "if Target is less than the Mid value, then from Mid values of the array have no importance".
yes, u said correct, if the target is less the we move towards mid-1 will be the end point ,and if the target is greater then we move mid +1 will be the start point.
Thank you for the video; I learned a lot. However, based on your explanation in the video, I believe the O(n) graph should be positioned in the middle, not below.
wow never thought I would ever have an idea on this, thanks very must. Am following your python course and I must say that the videos are very good, Mrs Telusko
In the following pseudocode, let A be an array of n positive integers, x be a positive integer number, start be an index, p be a list of integers, and result be a list of lists. a) Explain what the Mystery function does. b) Find an upper bound for its time complexity (T). Hint: You need to write T(n,x) as a recurrence relation and solve it by expanding it. function func(A, x): A.sort() result = [] Mystery(A, x, 0, [], result) return result function Mystery(A, x, start, p, result): if x == 0: result.append(p) return if x < 0: return for i from start to n - 1: Mystery(A, x - A[i], i + 1, p + [A[i]], result) anyone please help me with this ?
Can't be more grateful for this video🙏. Never seen a teacher like this.
You are the single greatest python teacher in the world, even Charles Severance can't teach as well as you. I watched so many videos on Big O but this is literally the first time I ever understood it
Keep up the good work! Please keep the DSA series on ongoing and also explain Time and Space Complexity in each of them. Your work is just AWESOME
Fantastic video, I am learning DSA for the first time and this video made so much sense to me. Thank you
thankyou so much sir i cant even express how you helped me by uploding this video i request you please complete dsa series thankyou somuch i owe you!!!!keep doing
Thanks for this video, you made it clear in understanding these basic things, which gives a clear understanding from now on. Thanks again
I have query in Binary search. As you said "if Target is less than the Mid value, then after Mid values of the array have no importance [8:37]". Why we count Mid value here for next loop ? We already know, Mid value is greater than Target value. It should be "if Target is less than the Mid value, then from Mid values of the array have no importance".
yes, u said correct, if the target is less the we move towards mid-1 will be the end point ,and if the target is greater then we move mid +1 will be the start point.
sir even ChatGpt is recommending your channel
Meeru Great Teacher Sir..
I was waiting for this video... please keep uploading..
I want to say thank you for starting this dsa series....i was waiting for you to start dsa..the way you explain gets fit into the mind...
Sir you're the best. Thank you sooo much for your kind support!
Hi Naveen
If you can cover Dynamic Programming..it would be great help
Please post more videos like this. I understood the concept of big 0 very clearly
Thank you for the video; I learned a lot. However, based on your explanation in the video, I believe the O(n) graph should be positioned in the middle, not below.
Big thanks to Navin Annaya ❤ maja aayega
excellent video sir , we want more videos like these
Really nice explanation!
Thanks you so much sir it's very helpful ❤❤
More videos on algorithms and dynamic programming please, and help us to make better projects
Good explanation but how we can take advantage with Big O Notation in case of unsorted arrays?
Amazing explanation ❤❤
Sir you are a hero
Best videi.Thank you
wow never thought I would ever have an idea on this, thanks very must. Am following your python course and I must say that the videos are very good, Mrs Telusko
thank you for existing
how do we do binarySearch if the target we're looking for is not a number?
thank you so much navin
Great Explanation sir❤🎉
Good morning sir ! Are you going cover all DSA topics here ?
I love you sir !
can we use a binary search without sorting the array
It will not work
God mode sir ❤
Super sir❤❤❤❤
sir thank you , please don,t ever skip this series or i will sucide 😩
In binary search the numbers are always in ascending order
thank you
Helpfull 🏅
Quite helpful 😇😇😇😇😇😇😇😇😇😇😇😇
Good evening sir.
Thank you sir❤
excellent
Please start paid course or give full list of dsa sir
In the following pseudocode, let A be an array of n positive integers, x be a positive integer
number, start be an index, p be a list of integers, and result be a list of lists.
a) Explain what the Mystery function does.
b) Find an upper bound for its time complexity (T). Hint: You need to write T(n,x) as a
recurrence relation and solve it by expanding it.
function func(A, x):
A.sort()
result = []
Mystery(A, x, 0, [], result)
return result
function Mystery(A, x, start, p, result):
if x == 0:
result.append(p)
return
if x < 0:
return
for i from start to n - 1:
Mystery(A, x - A[i], i + 1, p + [A[i]], result)
anyone please help me with this ?
nice
👍
♥♥
Second Comment
Now i feel like why this video ended so fast 🥲