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Euclidean Distance and Manhattan Distance
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- Опубліковано 4 вер 2024
- Hello All here is a video which provides the detailed explanation of Euclidean and Manhattan Distance
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Thank you, this is very helpful. Subscribed. One correction. It is not about developed countries, it is about America and Canada - newer countries, where cities were planned in this way - just a square grid. In Europe the cities are old, and the streets are convoluted, there is no grid in the cities. And the name Manhattan is because Manhattan in New York City is the most famous example of this grid pattern and skyscrapers. Keep up the good work!
It's not about newer countries. The grid plan has existed since the Roman empire (4th century BCE). They called it "centuriation", and ancient Alexandria had a grid shape. There are also many European countries which use the grid plan: Spain has Madrid and Barcelona, Italy has Naples and Milan...
@@PacoReer Thanks for pointing these interesting things out. I just checked Google Maps and Satellite View. My memory serves me right - I've been to Madrid, and it has no rectangular city blocks. Barcelona has some of them (I've never been there). Milan & Naples (also haven't been there) - kind of has some of them in very small areas but in general they are all skewed, criss-crossed with diagonals and also larger blocks are oriented radially towards city center, there is no single straight street that can get you across the entire city. American cities have far more rectangular plans with dozens of parallel streets and avenues. In an average street/block the concept of Manhattan distance will get you nowhere in Milan, Naples or Barcelona.
@@MykolaDolgalov Chamberi, Almagro, and many other parts of Madrid have a grid plan. Most of them have diagonals to help traversing from one edge to another. Barcelona has a street called "diagonal" that you can follow to get across the entire city. Just searching for "barcelona grid map" or "madrid grid map" already shows that they are indeed pretty regular-shaped, considering that, as you pointed out 2 years ago, they had to be built around old buildings.
Milan is another story, because as far as I can see it's more like a radial city plan.
PS: I live in Barcelona and we use Manhattan distance for calculating distance between two blocks
Just another info. The grid pattern is proven to be bad for cities as it creates lots of intersections that fill up with traffic (gridlock), especially near the center. New designs tend for a more complex system where you have main roads like arteries to move traffic between different zones of the city and smaller streets for local traffic. This means that if you cross a big city, you no longer need to pass an intersection at every single block, you simply follow the main roads until you are close to your destination and then you exit to the local streets.
Explained so well 👍🏼
You are definitely one of the best teacher of ML & data science.
I have seen your videos previously in the past as well & you always explain every topic with real world examples in simplest way possible.
Keep growing and shine more.
First time in life i able to understand this euclidean n Manhattan distance
No words to thank you enough. You make things very simple. This means you have understood the subject to its core. I appreciate you don't pass a concept without sharing its historical and scientific significance
Amazed by how clear his explanation is! Thank you Krish for sharing your knowledge!
I could never remember these formulas, which was which, and why. You made it very easy to make sense out of it. Thank you!!
Now i have a good reason to learn this.
You explained it well and pointed out it's usecase. Thank you ❤
You just got my subscription! Thank you straight to the point with easy-to-understand terms. Thumbs up Krish!
I'm from the United States, and your English is excellent. Plus the way you teach is really good that you make things so easy. Thank you for the help, and keep up the great work!
Hi..It would be very good if you could augment this with an example where we apply these distances in the ML algorithms. Thanks!!
Usually you would try both of them in a grid search, for example take KNN, try with K = 1,3,5,... metric Euclidean va Manhattan. Then you would have 6 choices and pick the best of them
ji, none of the developed countries have such a good explanation of Eucledian and Manhattan distance, thank you!
Fantastic explanation :) Cheers from NZ!
Explanation is very clear...you explain the concept in a very easy manure..thank you so much sir
check the meaning of 'manure'
Thanks, the practical examples are particularly useful!
ty indian dude, saved my studies about distance between points. regards from brazil
Very well explained Krish. Thank you for all your videos.
Krish, explained very nicely, thank you very much.
Loved it. First time here. Didn't get disappointed.
Great Video, Easy Explained , Thanks , Keep up the good work
This explanation is excellent. Simple math with real-world examples!
Amazing Krish, Concept clarity in few minutes👍
THIS GUY!!! you are just too much. The way you teach maths is like a story from Disneyland. I just love you. Thanks a lot
Great! I've never think that manathan distance is usefull until now indeed of we see it in manywhere. Math is cool when we know what it's for. Really thanks!
Excellent explanation Krish! Thanks from AU.
Thank you. I aced in calculus while in elementary school and the other week I heard of this term and didn't knew what it's all about. It's for a machine learning stuff that we start on looking into. At first few seconds your explanation, I recognized my long time friend of yonder past. Algebra and stuff like these. Thanks and I wished that people stick to familiar terms and not make it sound terrifying. The proper term should have been distance between two points and it would have sounded familiar. In fact, there is an additional variant to the concept such as geodesic points and stuff like non-Euclidean geometry.. Thanks for the clarification
Exactly !!
Wooooooowwwwww, I have never been more happier learning 😭😭😭😭😭😭😭😭😭
Nice and informative video. keep it up.
And yet again, I have been saved by a random Indian on UA-cam! +1 sub for you Sir!
thank you. Your delivery is really awesome.
Amazing and concise explanation!
Great! Thank you! Greetings from Brazil!
Bahut badhiya Kirsan bhai.
Extraordinary teaching!
Great amazing mind blowing videos
Thank you for making the subject so simple
Super clear ! Thanks a lot from France :)
Krishna..awesome explained. Thanks a lot
sir nice explanation and sir you missed the formula in K NEAREST NEIGHBOR but here you explained well sir. I am your biggest fan sir.
I like the way very much and to understand such things in native accents make the concepts more clear... Thanks sir ..
Excellent explanation!
You're an excellent teacher, thanks
Very informative and energetic.
First time watching your video, keep up the good work Krish!
Amazing content in this 8-minute video, I now fully understand Euclidean distance and Manhattan distance.
Most importantly I know how to apply to real question scenarios now, thanks again!
Thank you so much! You explained it so well in just an 8-9 min video!! Subscribed
greets from germany one of the greatest math explainings I saw on yt
Euclidean is displacement and manhattan is total distance is that so ?
What's manhattan distance? 3:40
Why it is called manhattan? 5:55
Application of both: 6:50
The Best Explanation 👍🏼
thanks, very good and interesting explanations.
thanks sir explained this topic, to be honest explained this topic very well....
Brilliantly explained Sir
Thank you 😊. Your explanation was very clear & easy to understand the concept.
Great explanation. Thank you. 🙏
using ur content as a primary resource for learning ML
bro your explanation is so effective I do like it.
Watching this when subscribers have crossed 800K, You rock
Very clear language and well explained. Thank you @krish
Thanks buddy. Cheers from Brazil
explained goood
congrats sir for 10k subscribers plz make vdo on how to get internship
Very well explained. Thank you
Thank you so much! This was brought up in an interview and this help so much.
Wonderful explanation sir
Love the energy. Liked and subscribed.
Thank you sir ! Short and straight to the point unlike college professors LOL
Great Explanation
thanks for germany. very well explained.
such a rare term to come up in papers, thanks for clearing it up for me bud.
Your teaching style is super clear and informative man -- thank you!
Thank you so much Sir .Very Helpful
Great Explanation.
This was super helpful for someone needed a very simple explanation. Thanks so much!!
Explained really very well
thanks alot you help me alot in my research
Very good video! Thank you!
I like your style man great communicator
Thanks so much; this is the exact kind of explanation I was looking for.
Thank you very much. This video is great
Very good explanation
Good explanation. Thank you
so many thanks really you have valuable information
Super sir thank you 🤗
superb explanation!! 👍👍
Thank you, this is very helpful.
Epiic sir ji 🙏
Very clear explanation thankyou
Amazing explanation
nice explenation. greetings from austria
Helpful content
In Euclidean distance it makes a lot of sense when you have 2 vectors(points in space). But with 3 points it doesn't make sense.
- x_1 is a first feature value
- x_2 is a second feature value
- (x_1, y_1) - is a vector of two data points
- (x_2, y_2) - is a vector of next two data points ( that we want to measure the distance to )
sqrt{(x_2-x_1)^2 + (y_2-y_1)^2 } - makes sense.
sqrt{(x_2-x_1)^2 + (y_2-y_1)^2 + (n_2-n_1)^2 } - don't make sense.
because you have n_2 - which is third feature value and n_3 which is fourth feature value.. You don't have a point in space, you only have two points on X axis without another 2 points on Y axis that way. I really can't understand that. It would mean that you can calculate this only if you have even number of features. Which is not true.
very well explained ! thanks
Brilliant video
great explaination
great explanation. Thank u
Amazingly done.
Thanks a lot for this explication I wish you all the best for the next
you explained it very nicely in the end that how to remember it , thanks .
Great video, thank you.
Very well explained and straight to the point.
great explanation thank you!