Good one. Is the world ready ? What do we call it. Dat-rap? Chip-hop?
@rbp3656 жыл бұрын
That's Lil O
@ChildishJordino6 жыл бұрын
haha
@mainpost41115 жыл бұрын
You're thinking of The Notorious BIG O.
@christinehill45847 жыл бұрын
Here's my favorite Big O analogy: Let's say you're making dinner for your family. O is the process of following a recipe, and n is the number of times you follow a recipe. O - you make one dish that everyone eats whether they like it or not. You follow one recipe from top to bottom, then serve (1 recipe).
@shubhamnegi19376 жыл бұрын
Chris Hill, good analogy. For O(log n) one dish is being served to all the groups or a dish for each group?
@B-Billy6 жыл бұрын
One dish per group.
@me-zz23406 жыл бұрын
O(n^2) analogy is not very good. I think if every person in your family makes individual dish for every person (so every person will have n dishes) - this could be O(n^2)
@spray-r99516 жыл бұрын
This analogy is fire!!!
@flybeep16616 жыл бұрын
Simon WoodburyForget I guess you don't know what an "analogy" is. You just explained it in your way without making an analogy at all. Using analogies is a way to describe complex concepts in an as simple as possible way. The simpler the explanation the better the analogy. You just explained it in a fashion you would understand it best which isn't necessary the best way for others. Making anlalogies circumvents this problem. I hope you're not a teacher, you wouldn't be good at it.
@joe448507 жыл бұрын
I might be too stupid to be a software developer. Unfortunately, I have learned this after 20 years of being a software developer. There are some things you need to know to impress people interviewing you that you may never touch on the job.
@fierce106 жыл бұрын
An older interviewer who was a director at a company failed me because he asked a question on this and he didn't know to drop coefficients. He insisted in the interview that its O(2N) and I got it wrong by saying its O(N).
@spray-r99516 жыл бұрын
You probably are
@rxtx39486 жыл бұрын
sometimes it feels frustrating that the interviewer knowledge is limited and he is just denying the same fact.
@danbo9676 жыл бұрын
My take on all this is this, if you work for a company that processes few records (entities, etc.) you usually are fine without complex algorithms unless you have to do complex operations. If the company processes a lot of records it becomes increasingly helpful (O(N)... did you get it ) to use algorithms and Big-O notation. Especially for companies that are algorithm intensive like Amazon, Facebook, Google, etc.
@funinchico846 жыл бұрын
No. It allows you to *prove* that an alternative is more/less efficient. If a developer can only come up with O(n^2) solution, then big O can tell you it's slow. Which is exactly what my computer can tell me with benchmarks. There's a benefit to knowing the notation, but it doesn't automatically make your code more efficient.
@lassulfi5 жыл бұрын
PTP - Pigeon Transfer Protocol
@akoshileolalekan53643 жыл бұрын
LOL
@FluffyNinjaUnicorn3Gaming3 жыл бұрын
YES!
@dakshdangwal3 жыл бұрын
ah yes
@seńor_t0072 жыл бұрын
I’d buy it😆
@mrkinetic2 жыл бұрын
But did they account for the time to transfer the data on and off the drive?
@user-gp8fr1nd3w4 жыл бұрын
oh my god for the first few minutes I thought it is an ad.
@CodeWithYubraj3 жыл бұрын
lol me too
@swissmatteo5 жыл бұрын
Even though I've had to survive from programming for all sorts of clients for almost 15 years, I now find myself having to learn these things if I want to settle down, get a job with a six figure salary. Truly nothing wrong with this, even though I've been told that I'm not a senior programmer. Which is correct, but I'm a senior in relationship development, sales, customer support, tolerance, fixing programming issues, doing whatever it takes to get the job done, and building real world applications. It's hard to tell an interviewer that has no real world experience these things without telling them to F off. I've disregarded my big Ego, and have been studying these things, taking online courses for Golang, and I now feel more confident that I can compete with my vocabulary and understanding of the computer science mumbo jumbo. It's truly an exciting step because after you learn just the bits and pieces, you indeed put yourself in a position to earn a wonderful living as a programmer. Wish you all the best of luck on your endeavors.
@PauloHenrique-pk5ro2 жыл бұрын
How you doin' mate
@swissmatteo2 жыл бұрын
@@PauloHenrique-pk5ro Absolutely phenomenal. 2022 brought along with it some new experiences and opportunities. And yourself?
@PauloHenrique-pk5ro2 жыл бұрын
@@swissmatteo I feel happy for you! I'm just an 18yo Beginner studying Basis Concepts to start Programming... Also trying my way to college, I'm nobody, yet. 😅 Care to share your GitHub Profile?
@สุภาพรสามงามเอี่ยม2 жыл бұрын
Absolutely mate i hope you're doing well!
@user-xx7tv7cc1y3 ай бұрын
I sympathise with you man, i joined a grad scheme years ago and all of the people i joined with all went our seperate ways and they made it through the ranks from fixing things here and there, doing some simple apps reading from a database and returning via an API. I did the same, but i always made sure to write as much code as I could. I even did coding tests online just to keep my skills sharp and do personal projects, even if they were small. eventually im able to get a 6 figure job because ive got real world experience but i also can program. all my friends who did less and less code as they went up realised that they were just working in average companies and just became knowledable about the systems they maintained, the second they want to go into the larger companies that are doing the best work and actually got asked engineering problems, they realise they had wasted 10 or so years doing maintainece work with the simple day to day getter and setter updates
@extremeloco236 жыл бұрын
Clicked this because it was 8 mins, straight to the point, no unnecessary knowledge. Loved it
@Ankit-zu2kp6 жыл бұрын
Yeah, I just hate to watch those one hour long explanations.
@jameswon54976 жыл бұрын
Thanks so much, this 8 minute video made it way more clear than several hours of lectures and readings
@Afrovo6 жыл бұрын
This makes me realize Colt Steele's a legend. I came here after watching his tuts on big O and I was surprised at how much I already knew
@theBIGgee4 жыл бұрын
He's d greatest
@akashgkrishnan95964 жыл бұрын
true that
@yongaisim68457 жыл бұрын
What a simple but clear explanation on Big O. I finally found you. Many videos start off with even more complex mathematical terms that are difficult to understand by themselves. You start very simply. Magnificent! How about one on Tractability to help.
@changeorbeextinct6 жыл бұрын
Great explanation of Big(O). This is important for any programmer to understand the efficiency of the algorithm. I know many excellent programmers who don't have CS degrees and may not know the academic description of Big(O). But they know it intuitively through experience. Having said that Bg(O) is an easy concept to understand, requires practice to know how to assess efficiency and scalability of the code.
@Rei-m3g Жыл бұрын
Nah
@Michael-AC3 жыл бұрын
Me: Man, I'm so confused by this class. What the heck is Big O? Gayle: Let's talk about one of my FAVOURITE things! Me: *feels even worse about struggling*
@michaeljeffrey53823 жыл бұрын
**fake laugh**
@latedeveloper78362 жыл бұрын
1:35 Describing the pigeon transfer speed in Big O notation 2:00 What Big O is as an equation - scales linearly with respect to the amount of input 2:10 Summary of Big O 4:35 4 important rules for Big O Notation 4:40 Why Big O is related to factorial (I think)
@howdoyouturnthison78272 жыл бұрын
For 4.40 : Cpu follow the steps one by one so you add them up.
@vincentbuscarello13578 жыл бұрын
Very strong overall explanation. What are the chances of getting a video showing some real world giveaways for more complex Os, like O(log N) etc?
@Jerkwaad7 жыл бұрын
O(sx)
@evantheking7 жыл бұрын
the chances are O(NO)
@igrewold7 жыл бұрын
Chances = Big O / 0
@bik83537 жыл бұрын
chances - Big NO
@hellolin3247 жыл бұрын
Binary search on an ordered array?
@JonathanMontgomery775 жыл бұрын
We need some O(log n) and O(n log n).
@shehrozeshahzad581 Жыл бұрын
The best video after spending hours I finally understood the big O!Thanks
@volo77 жыл бұрын
that introduction really helped put this subject into perspective
@sindhusasidharan67623 жыл бұрын
Thank You for this video. I reached here after checking many other links .This is the best .
@connergesbocker99027 жыл бұрын
Gayle!!! I just started reading cracking the coding interview and what a pleasant surprise to stumble upon this channel. Great educator and author. Thanks for the video :-)
@10uRization4 жыл бұрын
Although you left some other necessary o notations, your lectures are great! I'm glad i found your lectures, straight to the point and an understandable dialect.
@daramolapraise2 жыл бұрын
“DON’T BE LAZY!!!” is right. I was lazy for my Google interview because of the low stakes (I already have a job I am happy with) and fumbled almost every BigO question. It came up in every round. I knew which was faster intuitively, but found it hard to represent the correct notation. Learn this as it is very very important to fully grasp it. Also, know the BigO notations for most of the built in functions for your chosen language.
@jordi53163 жыл бұрын
i love this woman, she helped me so much
@mobileappmike5 жыл бұрын
Good video. People say McDowell's lessons aren't important and are never used outside of interviews, but big O notation is actually important. I learned this the first time I used nested for loops.
@MrMukulpandey2 жыл бұрын
Wtf.....watched so many videos to understand this concept....and here u are explaining the same topic in an easy way...❤️❤️
@rodrigosodre26552 жыл бұрын
In rule 3 you told the (for b) inside (for a) loop should not be O(n^2) but O(a x b) but the same structure in rule 4 you wrote O(n^2)
@samnik123456 жыл бұрын
Here is a my simple explanation for Big O Big O(1) :- The time taken is somewhat constant example 2x2 will take the same time to execute as 1million x 1 million. Or time taken to cook a recipe for 1 person is almost the same as time taken to cook for 5 people Big O(n) :- The time taken grows linearly as the data size goes up:- Example If there 10 people you have to cook for 1 person at a time from start to finish. so if it takes 1 hour to make 1 dish per person for 10 people it will take roughly 10 hours BigO(n^2) :- This is a bit complicated but imagine: Example if there 2 people you have to cook 2 dishes for each (total dishes=4). If there are 3 people you have to cook 3 dishes for each(total dishes 9). if there are 4 people you have to cook 4 dishes for each person(total dishes 16). If there are 5 people you have to cook 5 dishes for each person(total dishes 25). So if you notice the time taken is (n^2) Number of people (times) Number of dishes. BigO(n^3) :- Now look at this algorithm, Imagine there are 2 people For every person you have to make the same number of dishes like the previous example. Now add Alcoholic beverages to the mix, so if there are 2 people 2 drinks per dish. So if there are 3 people you will make 3 drinks per dish. 4 people 4 drinks per dish. If there are 5 people you will make 5 drinks per dish. Now calculate the total number of drinks for 2 people. Total Drinks = 2 people * 2 dishes per/person * 2 drinks per dish = 2*2*2 = 2^3 Total Drinks = 3 people*3 dishes per/person*3 drinks per dish = 3*3*3 = 3^3 Total Drinks = n people *n dishes/person*n drinks per dish = n*n*n = n^3 so the time taken for just the drinks, will be a cube of n( where n is number of people)
@alexwang9825 жыл бұрын
Samir Tendulkar Log explain?
@MrMrWazzaa4 жыл бұрын
HackerRank: Hi, Im Gayle Laakmann McDowell, author of Cracking the Coding Interview. me: i am aware
@srinivasnangunuri13137 жыл бұрын
Love your Graphics and Colors that are used for the Demonstration . makes it interesting to watch .
@spray-r99516 жыл бұрын
i agree!!!!!!!!
@Owen-6 жыл бұрын
HOLY SHIT, THANK YOU SO MUCH. So wish you were my lecturer cause this made so much more sense than anything he ever said!
@BillionaireDeveloper3 жыл бұрын
Such a revolutionary explanation of Big O.
@mikhailsidorov86894 ай бұрын
Thank you for such a good, short, and comprehensive explanation of the big-O notation. It was really helpful. I just wanted to clarify my understanding: according to rule 3 (different inputs => different variables), in the rule 4 explanation, there should be O(a + a*b) => O(a*b) instead of O(n + n^2) => O(n^2), shouldn't it?
@sollork81354 ай бұрын
Because it is same array it has same inputs so o(n*2)
@CaseyMartin2 жыл бұрын
I appreciate the bird moving at the end. Fun touch.
@kaieden7 жыл бұрын
The pigeon/Internet anecdote bears a striking resemblance the plot of Terry Pratchett's 'Going postal'
@himanshuk28734 жыл бұрын
"Hi, I'm Gayle Laakmann McDowell, author of Cracking the Coding Interview" "hi I'm gay lock MacDowell author of crack including interview" "hi I'm Dale lock McDowell author of Krakens pudding interview" "hi I'm Gail laughs McDowell author of Kraft encoding interview" "hi I'm Cale lack McDowell off of cracks and footing interview" "hi I'm Gaelic McDowell off of Cox encoding interview" "hi I'm Gail wok McDowell autocrats encoding the interview" "hi I'm Kayla Loch McDowell author of crack and cutting interview" "hi I'm Gail Locke McDowell author of crack and coding interview"
@matexxo40046 жыл бұрын
I've studied many ressources on that subject, but it's finally on yours that I got the concept. Cheeeeeeeeeeeeers!!
@CapnAhabChannel2 жыл бұрын
At 6:25 you say the nested loops are NOT N^2 but a*b. Yet at 7:24 you call the same nested loops n^2 and NOT a*b. Surely, both can't be right!? Have I missed something?
@nozzlium2 жыл бұрын
In the first example the code iterates 2 different arrays (a iterates arrayA, b iterates arrayB) that’s why they are represented by two different variables, while in the second exampe both a and b iterates the same array.
@thinhle13397 жыл бұрын
Very comfortable to understand. One thing i considered that: why we removed the instants -> O(50n) = O(n) ? Admit that the results wont depend much on instants but how ab the instant with >1000 ? It's matter.
@crewlylehintal94517 жыл бұрын
That's because you haven't studied Big O notation in depth. This video doesn't explain what Big O actually is or where it comes from. Big O notation is defined in terms of set theory. O of a function let's say g(n), O(g(n)), is defined as the set of all functions f(n) such that there exists constants c and n0, where cg(n) is greater than or equal to f(n) for some n > n0. Big O is not necessarily defined for algorithms, it's defined for all functions as an asymptotic notation. Edit: I suggest you study other asymptotic notations as well such as big Omega notation, theta notation, small o notation and small omega notation.
@jyrikgauldurson81697 жыл бұрын
That doesn't explain anything, that's just the formal definition in text which is better read in real notation. Also, sometimes constants do matter.
@JagjotSingh5 жыл бұрын
I studied this in my CS course 15 years back. After that I never got a chance to use it in practice.
@TheN0odles8 жыл бұрын
I'm from SA. I remember this 'exercise'. My brother even did a cartoon about it :-) Anyway, good explanation. Thanks.
@nistr27 жыл бұрын
I think it makes more sense to say you drop coefficients - not constants.
@mustafas1266 жыл бұрын
lol truuu
@espressothoughts6 жыл бұрын
Chris A. Both get dropped
@JoseAguirre-ri8tg6 жыл бұрын
Both of them get dropped.
@lancetschirhart76766 жыл бұрын
Both of those two things -- one, and also the other -- they both get dropped.
@wolfboyft5 жыл бұрын
n^2 = n * n, no constants|coefficients there
@mayank_upadhyay_195 жыл бұрын
Once, I used to thought that algorithm efficiency is not going to be a problem for me. ***believe me, I learned the lesson, hard way***
@hopeklein65374 жыл бұрын
How d'you find out? What d'you encounter?
@Wiejeben7 жыл бұрын
Thanks for giving an explanation that someone without much knowledge of maths understands by giving practical examples :-)
@scottishfoldmocha58752 жыл бұрын
The first rule contradicts the second one -if I have 2 loops 'a' and 'b' you are saying I need to add times -'a' +'b' , but then how come if I need to run SAME loop two times it is not 'a'+'a' but only 'a'??? I think first rule should be to take the longer loop: max(a,b). Your #1 rule is also contradicts to your #4 - dropping non-dominant terms.
@subhamengine11433 жыл бұрын
fav video for the concept.. gonna recommend to all my juniors.
@soham72264 жыл бұрын
Why Hackerrank is not organising contests anymore 🙄?
@johannsebastianbach34115 жыл бұрын
So, did Hitchcock make a DDOS attack in "The Birds"?
@lokeshwartailor82503 жыл бұрын
haha
@farisalsaad7 жыл бұрын
Question: You said in step 3 not to use n^2 for the two for loops that output the elements of the arrays (1,2). But in step 4 you use n^2 to describe the two for loops for the elements of the arrays (1,2). Why is that?
@qu4tschk0pf7 жыл бұрын
Faris Alsaad because in the first example they were executed one after the other and in the second example the first loop contained the second loop
@egan1087 жыл бұрын
in the first example, the loop is contained in the second. its the exact same scenario yet she used n^2 instead of saying a*b and i dont get why. can anyone explain why?
@santiagom77 жыл бұрын
Answer to this ?!
@mahwishj.68596 жыл бұрын
in example 3, you're checking each element in arrayA and then each element in arrayB. arrayA and arrayB may be of different sizes, therefore you can't assume that they're of the same size. so you do O(a*b). in example 4, you're looking for each a and for each b in the *same array*. that means that you're iterating through the same array and so it'll be the same size. so you do O(n^2)
@giannagrace63156 жыл бұрын
I noticed this and it confused me too, but after looking at both codes again I think that in step 3's code, there are two arrays: the first loop goes through the first array and the nested loop goes through the second array, counting how many elements arrayA and arrayB share, the lengths of both arrays are independent of each other (if a changes, b doesn't necessarily have to change). In step 4's code, there is only one array, and the nested for loop just ends up printing the different coordinate pairs of the array, there is only one array length, a and b are dependent on each other (if a changes, b changes)
@msesbreno3 жыл бұрын
Big O explained using a pigeon! What the heck! It’s so simple yet so effective that I want to cry. Thank you, Gayle! You are a gift to all programmers!
@awaisn5 жыл бұрын
i need this type of teaching. Fun, understandable and useful.
@chris93006 жыл бұрын
I enjoyed this. As a person who didn't have a background in Math or CS, this was very understandable. Now, I just need to remember and practice.
@ultimatesin35446 жыл бұрын
6:20 - you say it's NOT O(n^2)... 7:24 - you say it is.. I don't understand why in the first example you say it's not.. both of them are O(n^2) correct?? EDIT - oh nevermind I'm an idiot.. it's because in first example both arrays may be of different length, in second example it's the same array so same length..
@mustafas1266 жыл бұрын
6:20 is 2 arrays possibly diff size looped through so a*b and 7:24 is the same size array looped so n*n or n^2
@Chiving6 жыл бұрын
Thanks mustafa!! :)
@boyracer30005 жыл бұрын
Don't worry she didn't explain it very well.
@alexandruberende66825 жыл бұрын
Thanks for the EDIT , because i was thinking the same :)) .
@liamlindsay60824 жыл бұрын
Ah, this confused me too
@stephenday48342 жыл бұрын
This is a wonderfully clear explanation.
@marie21366 жыл бұрын
Wow, Thank you sooo much! This video helped me a lot for studying for my finals.
@Lokaine013 жыл бұрын
You had to be an amazing note taker in school. Thanks for the explanation
@thekrisho7 жыл бұрын
7:13 function whyWhouldIDoThis(array) {return lol;}
@CJRH1FILMS3 жыл бұрын
Error: unused variable. 'array' is not used
@stefkodak3 жыл бұрын
I really love this video, they really did a great job here.
@francisaiello61976 жыл бұрын
Gayle - I'm curious what tool you used for drawing the various slides. Looks like it might be a freehand drawing tool and looks great.
@CoryTheSimmons7 жыл бұрын
If I understand this right, we should run benchmarks when nesting loops inside of loops (add more data to our tests and see if the increase is exponentially rising). It's really easy to exponentially slow down processes, and there's usually a clever, more performant, path.
@tear7287 жыл бұрын
An easier way to do it is to find the complexity of the algorithm mathematically and then from there on you know exactly what you're dealing with.
@LBC_squared3 жыл бұрын
Such a great explanation. I can flip a string with xor but I couldn't get Big O for the life of me. The meaningless N got me so confused before. Thank You!
@music-jj2pl3 жыл бұрын
So we use meaningful variables in the Big O notation not always n - cool. Next example @7:35 has a and b variable with no n variable and the answer is ... Big O (n^2)! Shouldn't it be Big O (a*b) ?
@victormoura72763 жыл бұрын
I thought the same as you buddy.
@GlynNormington2 жыл бұрын
Very good, thanks. Please note that sometimes people pronounce O(1) as "order 1", O(n) as "order n", O(n^2) as "order n squared", etc.
@billbottletop51402 жыл бұрын
that pigeon analogy finally made it click for me.
@inframatic7 жыл бұрын
I have seen this and read Cracking the Coding Interview 6 and this explanation is far far far superior, but the book explains O(log N) and more complex algorithms
@samr67814 жыл бұрын
Does the square plot look like a rectangle only to me?
@momentouscrazynoob17092 жыл бұрын
thank you! It really cleares stuff up :D
@tekamanurag60652 жыл бұрын
This is what I needed to level up thank you soo much.
@ButerWarrior443 жыл бұрын
so this vid was for time complexity not space complexity?
@allanhenriques26944 жыл бұрын
you use non dominant dropping when you take the run time of the nested for loop itself right?, it should be a*b + a and you drop the non dominant 'a' to get O(a*b). You should explain that earlier, but fantastic video
@princeOalgeria3 жыл бұрын
So it's about how many times the function scales, and not how much time it takes to run
@MPKDilshan Жыл бұрын
Thank you and it is really helpful.
@vishalsoni64093 жыл бұрын
Excellent explanation! Thanks for simplifying Big O concepts.
@davidkumarr Жыл бұрын
why at 6:53, the complexity is O(a*b) not O(a+b)? based on 1. different steps get added wont this just be adding?
@Fan-fb4tz4 жыл бұрын
This is the clearest intro on Big O
@amirmustafa6224 жыл бұрын
Very well explained mam
@krissaurixsent79883 жыл бұрын
Great video, good theme the big O notation is very interesting
@stoopydmynd3 жыл бұрын
Finally a good explanation! Couldn't understand it with my lazy ass teacher... Thank you!
@Raedabk-q6r Жыл бұрын
i like the animation, how can i do something similar?
@jessicalaursen17906 жыл бұрын
Straightforward. Easy to understand. Cool graphics! Hats off =)
@nanophyr_44684 жыл бұрын
Nice point to highlight at 6:23 .. it's small but I caught out doing this in an interview before.
@RadicalCaveman5 жыл бұрын
3:20 Always good to see someone who knows how to draw a square...
@hanats4 жыл бұрын
it is a square, just not drawn to scale.
@FeLiNe4184 жыл бұрын
perspective
@santoshsco2 жыл бұрын
Thats a great explanation , supercrisp and helpful for interviews .
@AzaIndustries5 жыл бұрын
This is killing me right now in CS... I dropped out of school due to illness and did a test to get into uni years later. I know I can code and test the efficiency of my programs using these theories in practice. But if it ever gets asked of me in a interview to explain the proper math terms and lingo I'm screwed. I'll get it now but in the future I won't remember this stuff, I'll only remember the practice I've had with actual algorithm implementation and refactoring.
@nbl235 жыл бұрын
if the example at 4:55 is O(a+b) then why is the example (the top one) starting at 5:26 O(n)? Running thru the array for finding Min value first can be looked at as doStep01() and then running thru the array for finding Max value can be looked at as doStep02() thus becoming O(a+b) here as well. How did that become O(n) ?
@alexmeyer23945 жыл бұрын
Finding max = O(n), i.e. a = n, finding min = O(n), i.e. b = n, now combine it: O(a + b) = O(n + n) = O(2n), then drop the constant = O(n)
@vterrans5 ай бұрын
How did printing pairs became O of N2?
@ll-sz9fl4 жыл бұрын
Thank you very much, better than my CS PhD. Professors.
@jeanliu67626 жыл бұрын
A very concise and to-the-point video. Thanks!
@AdrianLParker3 жыл бұрын
@7:40 Why does O(n + n^2) reduce down to O(n^2)? I found the wording of rule #4 to be very confusing.
@AdrianLParker2 жыл бұрын
@@AEROPHIL100 I know it's a bit abstract in the first place, but isn't reducing to the dominant term making the result wildly inaccurate?
@ThiruSings7 жыл бұрын
Finally I understood Big O - Thanks a ton !!
@rishikeshsarangi12454 жыл бұрын
Thanks , the concepts are now clear , time to solve questions
@izavala4 жыл бұрын
i loved the example
@kris41173 жыл бұрын
Well explained about representing O as a function of N under different scenarios.
@ritickmadaan4 жыл бұрын
Its a really helpful video, made the concept pretty clear the only one thing is that it would have been better if an example of O(log(n)) would have also been there
@arthurmazzi8412 жыл бұрын
Very nice video!
@jiayouchinese5 ай бұрын
Wasn't Big O an anime about a big robot?
@dreablin2 жыл бұрын
Good explanation. but texts are nearly unreadable because of the font :(
@defense200x7 жыл бұрын
But that if the physical storage media is too big so the data has to be split across 2 or 3 usb sticks which the pigeon can't handle at once, so it would have to fly twice or even thrice
@RadicalCaveman5 жыл бұрын
Not to mention if it's also carrying a coconut...
@zato8286 жыл бұрын
What the heck. I was reading her book and I went to KZbin to reinforce the concepts and this was the first video I picked.
@Jemmeh6 жыл бұрын
Same. GAYLE ARE YOU WATCHING ME ;A;
@alexandergonzalez59756 жыл бұрын
Do you recommend the book?
@sufjanr90336 жыл бұрын
Sane here 😄
@kickbuttowsk2i5 жыл бұрын
this event occured to me now
@xMercuryx562 жыл бұрын
5:05 “walks thru da udder awway”
@nathanaelbennett82865 жыл бұрын
Great explanation of Big O but for the love of god please use a readable font for those coding snippets.
@FreedomOfTħought3 жыл бұрын
Big O notation only exists to put across a formal and tangible argument in support of why one solution is more or less efficient than another. On its own, there is no benefit.