Linear Algebra for Machine Learning: Dot product and angle between 2 vectors Lecture 3
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- Опубликовано: 11 окт 2024
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dude way better than those linear algebra books, understood 100% did not even have to take notes, very intuitive!!!!, thank you man!!!
Very good way of teaching super se bbi uppar
You are great sir, very nicely explained each concepts
ur handwriting is nice
simple and easy explanation. clearly understood. thanks lot..
Why mostly Dot Product is used in ML/DL/AI than Croos Product ? What is the intutive thought of dot product ?
Great channel, keep up the good work!
thanks really helped
I think I might have a correction for you. if a dot b = 0, you say the vectors must be perpedicular. Well, what if one or both of them is the zero vector? a dot b = 0 guarantees that the two vectors are ORTHOGONAL. not necessarily perpendicular. I think.... let me know if I am wrong. Thanks for the videos!
“In geometry, two Euclidean vectors are orthogonal if they are perpendicular, i.e., they form a right angle.”--Wikipedia.
en.m.wikipedia.org/wiki/Orthogonality
@@AppliedAICourse no dispute there. BUT orthogonal can ALSO mean that one of the vectors is the zero vector, and thus not perpendicular
In ML if we know that two vectors are perpendicular then what can we infer from that sir? Can you tell a real world use case.
This will help you in defining a plane which is used to separate points of various classes in many ML algorithms. We explain this connection in our course videos in detail
Say you made an awesome product and now putting youtube ads (Vector A) for promoting that product. Say every day you're putting more and more money in youtube ads, but when you check the number of the product (Vector B) sold, is same say only 5 products per day.
your data might look like this
Day, youtube_ads(Vector A), #product_sold(Vector B)
1, 30$, 5
2. 50$, 5
3, 45$, 5
4. 70$, 5
..... and so on. You see you're putting a lot of money on ads, but no change in the number of products sold. Ads can be vector A and the number of products sold is vector B. It seems Vector A is perpendicular to Vector B. Vector A is not at all aligned in the direction of vector B.
A.cos90 x B = 0 (dot product is 0)
Find more math for ML here: ruclips.net/user/mirrorneuron
Sir addition of two vectors have to be done by parllelogram law how can u add them straight forward ?
whats is significance of angle theta with respect to machine learning perspective??
We discuss that in detail in other videos on how this angle is used in ML. Simply put, one thing you could do is to use it to compute how angularly farther away they are from each other. We use it to define something called a cosine similarity used extensively in ML.
@@AppliedAICourse Thnx for the reply.. actually im looking for it and trying to understand cosine similarity and tf-idf. 😀
Can you give me that "other video" link that you mentioned in the reply???
You can see all of our free videos on AppliedAICourse.com by simply registering. All of the free videos are in a neat sequence on our website which will help you see many other videos where these basic concepts are used extensively.
What is the use of dot product..also why we need to take cos ..not sin..
here is a detailed explanation why Cosine
math.stackexchange.com/questions/1149199/why-do-we-use-cosine-as-the-expression-of-vector-dot-product
simply said, dot product determined how much two vectors can result value(the kind of value depends on the problem like value of revenur given from 2 vector represent each item maybe banana and apple, with x is amount each item sold and y is prices of each item)).
and cos is used for finding the projection of one vector to another vector, see this ruclips.net/video/KDHuWxy53uM/видео.html
6:27 owww, a little aggressive here