Do you need to know math to do machine learning? Yes! The big 4 math disciplines that make up machine learning are linear algebra, probability theory, calculus, and statistics. I’m going to cover how each are used by going through a linear regression problem that predicts the price of an apartment in NYC based on its price per square foot. Then we’ll switch over to a logistic regression model to change it up a bit. This will be a hands-on way to see how each of these disciplines are used in the field.

Code for this video (with coding challenge):

https://github.com/llSourcell/math_of_machine_learning

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Like a nice……. Ball. Hahahahahahahaha

Thanks for such a great comprehensive explanation of math in machine learning. That really helps to understand what kind of math I need to learn. š

All this look like mumbo jumbo š Hope I will get the real meaning One Day š¤

How you can understand this !!!

Great video!

We have a Post Doc Position to work with Machine Learning (May 2020)

http://www.fapesp.br/oportunidades/machine_learning_for_interpretation_and_analysis_of_microscopic_images/3639/

Hi sir, have you ever used "Eviews"? I was able to do all this staff on it, then it means I know ML?

For data analyst do you need maths if so what maths is required plz assist I haven't seen a single utuber explaining preciously regarding math and till which level can u plz help

Wow

You are one of the best ML of youtube . It is so hard to find information on the russian .Good luck for your business .

every time i try to do linear regression i stuck at gradient descent.

Nice.. btw do you have any playlist in which you teach all the math required for ml? Or give me some references from which I could learn it?

Clear and concise. Great content and explanation9:18 linear alegbra

Excellent. Thanks

What you did in this video is totally overacting…Looking so foolish…Best thing is ur hairstyleš

He is fraud

Thanks brother

Sounds like when someone talks about machine learning knowing only high school math

A student will always be a student.

So this Fall Quarter 2019, I'm getting ready to finish Calculus I in college which taught me how to work with Toolkit Functions, Derivatives, Limits, Domains, Ranges, Power Rule, Quotient Rule, Product Rule, Chain Rule, L'Hopital's Rule, and Logarithmic Properties. My question is….do I need to take Calculus II and III to be able to understand the algorithms used in Machine-Learning? Because I would much rather be taking more programming courses. I'm already familiar with some ML functions like Sigmoid, ReLu, and TanH; but I have not yet built my first artificial neural network. Personally, I enjoy Statistics more than Calculus, so I'm hoping that I don't need to take more Calc courses to be successful in this field. I've already taken Stats 1 which taught Standard Deviation, Variance, Distribution, and a few other concepts, but it didn't cover Linear Regression and my Calculus course hasn't covered Gradient Descent. If there are only a few more essential topics for the math used in ML, then I can learn on my own if I know what to study.

What is the best software engineering career path for a teenager who is very strong at math? My son is 16 and did linear algebra all the calculus courses (multi variable and differential) and is in transition to higher math (proofs) and decided he didnāt want to become a mathematician. This is my search. It seems machine learning is really relevant but I donāt have an advanced math background so Iād love to hear your input! Thanks so much.

0:25 I like this pic about object as example lol

Hello world for sir fraud