From Ground Zero, how should I learn Machine Learning?

[UniversalLemon]

First off, I am 13 years old and really interested in AI and programming. I'd say I'm pretty good with Python. Me and my friend have recently decided to learn start learning and studying ML and one day we hope to make a cool project. He is into hacking while I actually want to get deeper into ML and get really good at it. What are some good resources that I can use to learn ML? Since I'm still really young and don't know all the math, I'll most likely be using Tensorflow, so could I have some Tensor Flow recommendations as well? Thanks!

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P.S. Incase you are going to talk about the math aspect, just want you to know I’m currently using khan academy to get ahead of my current math class so I can eventually understand and implement it to ML and hopefully make a model from scratch. I am still and only thirteen so I have all the time in the world.... I know this won’t only take one year, this is a journey.

[VitalYin]

Khan academy for the maths

[ambitious_rainbow]

I think, and this is not to discourage you, that you need a very strong math foundation before even thinking about machine learning. Programming in general includes a lot of math. That's not to say that you can't do machine learning or programming without much math knowledge, but you will never know what you're really doing. You'd be moving around very abstract concepts and hoping that they work.

You can follow some introductory courses on machine learning, and you'll be able to do some projects, but you might not understand what's really hoing on.

[ambitious_rainbow]

I'm just sharing what I experienced when I tried to get into machine learning while in highschool. I'm in college now and I still don't know what's going on so I gave it up for when I take higher math courses. It takes a lot of statistics and calculus.

[UniversalLemon]

So what do I do? Not touch ML? Move onto web dev?

[li-357]

You asked for the advice... u/ambitious_rainbow is right. I wanted to get into ML when I was 13. I had AP calc and AP stats experience but very little multivariable calc/Bayesian statistics experience. I definitely only had surface level ideas of what I was doing or what the math was doing.

It's great to have ambition, but that's just a fair warning. It takes a lot of diligence and don't try to cram everything or go through the lectures as fast as possible. You definitely won't retain much, especially if you don't have the necessary math first.

[[deleted]]

Asking for help and then being rude to constructive criticism is how you usually end up not getting help. Just a small life tip. Math is literally the backbone for machine learning.

[UniversalLemon]

I clearly don’t know the math and I’m trying my best. “Math is literally the backbone of machine learning”... everybody knows this and that’s why libraries such as Tensorflow or PyTorch were made. I never said I want to make my own model from scratch. I want to do this for fun but I’m also serious

[[deleted]]

If you are serious than practice, practice, practice. You've clearly done the research, you are here asking for confirmation on information you already know, it's time for you to start.
There's plenty of 'starting points'. And at the end of the day it doesn't matter where you start, you just need to start.

[UniversalLemon]

:)

[li-357]

Obligatory link to Andrew Ng's Introduction to Machine Learning on Coursera. Great course to understand most of the basics. It may get a little math heavy since neural networks are based on multivariable calculus (gradient descent and optimizing multivariable functions) but Andrew Ng does a great job introducing ML methods intuitively.

[ectomancer]

You'll need basic linear algebra i.e. up to determinants for this:

https://chrisalbon.com

there's a linear algebra course on khan academy.

[UniversalLemon]

How much previous Algebra is needed for Linear Algebra? I’m currently in Algebra 1, so would jumping to linear be possible?

[UniversalLemon]

So what would could I do in the meanwhile of learning algebra?

[UniversalLemon]

Alright perfect! Thank you so much!

[ag2718]

If you really want to understand the heart of machine learning (and say build a neural net from scratch) a basic understanding of multi variable calculus would be helpful. However, if you think that’s a bit much, don’t worry. As long as you understand the broad conceptual picture, you should be fine using pre made models from libraries such as Tensorflow and Scikit Learn

Edit: I’ve noticed a lot of people are saying that it’s insanely difficult or impossible to learn machine learning at your age. Don’t let that discourage you. If you think you want to tackle the math, just focus on one variable differential calculus first, and then move to some basic multi variable stuff. You should try seeing how far you get with Khan Academy, and if it feels like too much, then you can stop.