Machine Learning is Just Mathematics! Free Machine Learning Resources

Here are some free machine learning resources. In this I explain that Machine learning is really just mathematics and I explain what type of maths is needed to learn machine learning and I give you some great resources to learn it.

WANT TO LEARN PYTHON? Here's my course:

#MachineLearning #LearnMachineLearning #MachineLearningMaths

[mostafaEOY]

spend the time and learn the math. Best part, bec people always tend to forget that. Well done Sir

[CodeEmporium]

I cannot express how right you are. I upload videos on Deep Learning & Machine Learning, and through these videos I explain the Math behind how complex algorithms (and research papers) work. However, I _always_ get the "so where is the code?". And even if I do a tensorflow version, I get "Can you do this in pytorch". No point in programming if you don't have a firm grasp of the concept involved.

[josefortyfive]

Khan Academy also have tutorial for Linear Algebra. Also, he has a tutorial for single variable, and multi variable calculus in his website. And, IT'S ALL FREE!

[modelworkzseo]

seriously: why isn't your channel blowing up?

[ElColombre]

I'm a math student and I've just discovered this channel, being curious about programmation, ML and AI. This video has given to me excellent news, thanks!

[shamimibneshahid]

I just love your simplistic style with no mumbo jumbo

[cesarMade]

I've been reading Introduction to Statistical Learning for two weeks now and I did a couple of courses from Coursera (the ones by John Hopkins University), and I was not sure whether I was on the right path, but your videos gave confidence that I was on it! Thanks!

[ranausamaali]

Sir you deserve million of subscribers with million of views

[huberts]

i really like your point of view. I get really motivated. I started 2 years ago my MA at Econometrics/Data Science, but with BA just in Economics. What I primarly learned during last 2 years, is that there's a lot in front of me to learn, but it also started being exciting. I can't wait to graduate program soon, and have more time to catch up with where i really feel deficiency to go further.

[nikosmparoutis]

1) To understand algorithms, data structures and parallel computing, cloud 2) coding-debugging in Python, R, Java, Scala 3) math logic not math techniques 4) statistics 5) control systems
0) Can do all the above together APPLICABLE

[shrivardhinitalule]

You are no less than Khan Academy when it comes to python. Love the library in the background.

[MattUKepcc]

Thank you! I am taking Machine Learning with one of the smartest but toughest professors in my CS department and I feel more confident!

[raghuwanshraj]

I can't tell u how u much u have inspired me now
Cuz just now I got frustrated from maths behind backpropagation.
I always thought of doing the maths first before going to implement it.(I mean it, it kind of make me more confident of what I know)
But seeing my friend who just code it on python and get the result faster without diving into maths upsets me also.
But from now onwards I will confidentially devote my time behind its mathatematics.
I have watched linear algebra from 3 blue 1 brown before coming to this video(amazing technique of visualisation).
Thankyou god for telling me that I am doing all right!!
Thanks for the

[adoniskomplex]

I totally agree. It's Maths applied on a computer.

[sifat]

Finally someone spoke some practical things about ml.

[TheAgentOfDeath]

Probably the most helpful channel for aspiring data science students. Very informative and useful unlike the other popular videos on data science.

[videocorner]

Sir please give those links in description
I think you are the only person on youtube who can guide us to the right 👉 direction
Please sir we need those link
Thanks
May you live long

[randomfun]

damn this is so underrated .
you are going to grow soon .

[tonyfondacaro]

My favorite part of this community are the folks who are generous with their knowledge and experience, enabling others to follow in their footsteps.

[thecatbellayuki]

No resources in the description 😕 please provide the links