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Why is linear algebra truly helpful? There very many functions of linear algebra. In knowledge science, particularly, there are a number of ones of excessive significance. Some are straightforward to know, others not simply but. On this lesson, we’ll discover three of them:
• Vectorized code also referred to as array programming
• Picture recognition
• Dimensionality discount
Okay. Let’s begin from the best and doubtless essentially the most generally used one – vectorized
code. We are able to definitely declare that the worth of a home is determined by its measurement. Suppose you realize
that the precise relationship for some neighborhood is given by the equation:
Value equals 10,190 + 223 occasions measurement. Furthermore, you realize the sizes of 5 homes 693, 656, 1060, 487, and 1275 sq. toes.
What you wish to do is plug-in every measurement within the equation and discover the worth of every home,
proper?
Effectively, for the primary one we get: 10190 + 223 occasions 693 equals 164,729. Then we will discover the following one, and so forth, till we discover all costs.
Now, if now we have 100 homes, doing that by hand could be fairly tedious, wouldn’t it?
One approach to take care of that downside is by making a loop. You possibly can iterate over the sizes, multiplying
every of them by 223, and including 10,190. Nevertheless, we’re smarter than that, aren’t we? We all know some linear algebra already. Let’s discover these two objects:
A 5 by 2 matrix and a vector of size 2. The matrix accommodates a column of 1s and one other – with the sizes of the homes. The vector accommodates 10,190 and 223 – the numbers from the equation.
If we go about multiplying them, we’ll get a vector of size 5. The primary factor will probably be equal to:
1 occasions 10,190 plus 693 occasions 223. The second to:
1 occasions 10,190 plus 656 occasions 223. And so forth.
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#LinearAlgebra #Math #DataScience
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Good explanation
I am so happy I never learned this.
It is more boring than watching the grass grow.
If you make video games, you never have to ask if linear algebra is useful.
lmao what ghetto do you live in lmao add a zero to all of them
I reject the premise re the first example re real estate. The first part of equation is likely off by a lot because no one wants to admit where there actual lines of value are in terms of where people put value. Zip codes are NOT proxies for real value.
Good explanation
That's it tis is the video I was looking for.
VERY NICE
thank you very much
why is linear algebra called linear algebra, rather than, say, digressive matrices, or patterned collections
I’m pursuing data science as my major n trust me linear algebra is v important if you want to be on top of the game👏🏽
Don’t take it leniently
Nah
I dropped out of an IT university years ago, because for months and months we were studying and solving dry higher math problems with the thought that "one day we will see how it's used in real life". I sucked at it, because I didn't like it and didn't understand the principles.
Teachers only gave vague answer to the question "Where will we use it?".
Being a visual learner, had they shown me a video like this, not only I'd be eager and excited to learn it, but also all of of the methods and principles would make sense.
Thanks, and it's so easy & simple!
quite good, thanks, but in RGB, B represents black not blue
Great video, but a word of advice: Anything and everything you can learn about is useful.
In the first example, what variable would the column of 1's represent if the others represent the size and the constants of the weighting vector? Could it be used to index a house id # or something similar? Or does it need to be all 1's? Great video!
whoah, theres nothing in the video!
Why am I a seventh grader watching this???
This is great. Mainly because it explains the reasons behind a needed knowledge.
It's bad to just say: you need to know linear algebra ok?
Why? This video explains a lot. I'll look for further information about it. Thanks
pretty interesting!
Brilliant
This looks like a typical Fortran program using Do loops.
Really awesome, thank you for this clear explanation.
2:20 Isn't it plus 223 times 693?…
I am not sure I agree with 'vectorized algorithms are faster'… In python yes, but in general probably not.
Excellent.
"We know some linear algebra already don't we?"
Uh….no, no we do not.
Thanks for the video. I’m prepping for a data science bootcamp and it helped to get me reacquainted with some of these concepts
Awesoem
USing ladmarks is actually better for navigation because the brain dosnt operate in scientific units of measurement.
Amazing stuff! It's always important to have clear answers for "why do I need to study this"
Wedteriills.Wedtaara.Wedtisldre.Wedtaara.Wedteta.Wedtaara.Wedtambar.Wedtarva.
I Love your videos
I wish it would longer