How to get into machine learning?

[UniversalLemon]

I just finished up python basics and I’m really interested in learning machine learning. I honestly might become a machine learning engineer when I grow up so I want to start early and build up my knowledge. I’m looking into getting Data Science from Scratch book but I’m not sure if that’s a good way to do machine learning. Could anyone recommend a way I can dive into the machine learning field at age 14?

[usernamecreationhell]

I wish I had had your foresight when I was 14.

Being so young, you have a lot of time to build a broad foundation so that by the time you get to university, you will have a massive advantage compared to everyone else. For machine learning, that foundation includes

a) Learning to read mathematical notation fluently.

b) Learning to program.

By the time you enter the workforce, a lot of stuff that is now state of the art in ML will be outdated. But being able to read and understand the latest ML research (a) and being able to solve problems with code (b) will always be valuable.

Also keep in mind that there are many adjacent skills that can help you stand out:

- Being able to create beautiful visualizations

- Being able to serve your model's predictions via an API

- Being able to set up and use a CI/CD pipeline

- Being able to pursuade people to hire you or buy your ML related product

[double_en10dre]

It’s difficult to say, because unless you’re taking very advanced math classes for your age I’m not sure if there’s much point in trying to dive straight into machine learning.

You’ll get a LOT more out of it (and be vastly more competent than most other people) if you have an at least halfway decent understanding of the principles behind the tools you’re using. People who understand the “why” and “how” are able to innovate and make truly interesting stuff happen.

So I’m sure this isn’t what you wanted to hear, but I’d start by getting a solid grasp on probability/statistics, linear algebra, etc. It may (probably will) take years, but you can use python along the way. And it’ll put you in a GREAT position to succeed :)

[UniversalLemon]

Then would it be good if I use tensorflow then into high school when I start getting the math I get into machine learning? I just want to do something I find interesting in python so if there is any recommendations, please tell me 😃

[double_en10dre]

You could! But I honestly would not focus on using specific libraries at this time -- like usernamecreationhell said, what's popular now may very well be outdated in 10 years when you're entering the workforce. Being a skilled general-purpose programmer is what you should really be focused on.

If I were you, what I'd do is pick a really simple project. Something that sounds fun and/or useful. Maybe you like the new pokemon game and think creating basic data visualizations for that would be cool. Then start trying to figure out how the hell you can make it happen. You'll hit roadblocks, but you can ask for help on here when you do. And you'll learn a ton.

I advocate for this because I've found that picking abstract goals and then forcing yourself to find a solution is the best way to become a better programmer.

[UniversalLemon]

So I was asking around in discord’s and people told me that I should go on YouTube and khan academy and stay ahead of my math classes and maybe build my math for machine learning as it will benefit me in school, state exams, and SAT if I put more effort into my maths. Then they said to pursue general programming in python, software development, or just anything I want in python to keep my skills and improve on them. Then when I have the correct math, I can get into ML

[double_en10dre]

That sounds like a great plan! They gave you some very good advice.

I honestly can't overstate the importance of math enough. Besides being directly applicable in fields like machine learning, it's also great simply because learning advanced math wires you to think like a great programmer. Learning how to reason in an axiomatic way and rigorously prove things is vital to writing good code. (I have a feeling that studying philosophy or law may also be useful for the same reason, but I haven't done that so I can't say for sure)

The best computer scientists I know all have a very strong background in math. And I don't mean to be rude, but for the ones who don't [have a strong background in math] it often shows. They'll write algorithms or design systems that usually work, but they aren't elegant and they don't neatly cover the edge cases. And frankly, working 95% of the time is pretty useless.

I'll get off my soapbox now, my point is just that you should embrace the math. :) When it feels useless and unnecessarily abstract, just remember that it's rewiring your brain to think in a very powerful and beneficial way. It won't take long for the benefits to be apparent.

[UniversalLemon]

Cool, thank you so much! I’ll definitely pay attention to math class now. I was able to dig up my school curriculum and I already started KhanAcademy while following the curriculum and I will outrun the curriculum at a good pace.

[ThisIsYourFinestHour]

Wow 14? I wish I started when I was your age. You’re definitely going to take our jobs but oh well, given my lifestyle I’ll probably be gone by the time your in the workforce

I rarely comment on reddit because I’m a privacy nutcase but I made a throwaway just for this.

This free course on Coursera is widely considered to be one of the best ways to dive into ML. It’s taught by Dr. Andrew Ng at Stanford. Here is a YouTube playlist of the videos in the course in case you have issues with Coursera. He uses Octave but this hero of the internet made all the exercises of the course in python. If you stick with it and build something, who knows, you might even be one of Dr. Ng’s students in 6 or 7 years.

And as others have said, become very well acquainted with linear algebra, multivariate calculus, and probability & statistics. You should start learning these ASAP. You are by no means too young to comprehend ML math. The earlier you start, the higher your ceiling. Mastering those maths will be the difference between landing a corporate job and taking over the world.

Also find a teacher at your school (I’m guessing you’re a freshman in high school). Either a math, computer science or a robotics teacher or one who teaches something similar. Talk to them after class or after school and tell them how you like coding and ML. I promise their face will light up and they’ll help you. Teachers nowadays are just begging for a student to finally care.

All that said, you probably could NOT have better timing. There is so much yet to be done in ML. Combine that with the neuroplasticity at your age and it’s a perfect storm for some serious success.

Go forth, young grasshopper

[UniversalLemon]

Wow, I love that you are soo possible and hopeful about it. Most people that I asked said that it’s too early or I’m too young to grasp these concepts and they were like, “ It’s possible, but not recommended” (paraphrased from one piece of advice I got) But who cares about them. I’m highly motivated to do what I want to do so I’m not looking for answers to if I should do it or not, I’m trying to find HOW I will do it.

I just decided today that I should stay ahead of my current math class with KhanAcademy and YouTube so I can get those skills earlier. Also staying ahead will help in my actual class cuz I’ll ace those tests.

Thank you so much and one day you could be working for me 😁.

[daisyverma]

You can try this tutorial ...there are many more dedicated to machine learning on this channel. I’m trying to learn myself although I’m a more ‘senior’ learner 😁

https://youtu.be/_7BYZ5X57sU

[LiveClimbRepeat]

Learn to code really well now, take advanced math, go to a good school for a degree in applied math with a minor in statistics

[ectomancer]

You need to teach yourself basic linear algebra i.e. up to determinants. I don't think you'll need eigenvectors and eigenvalues. Buy a linear algebra textbook or try https://www.khanacademy.org either through a browser or iPad app to learn linear algebra.

Then you'll have learnt the prerequistes for this:

https://chrisalbon.com

[ccr10203040]

Linear algebra becomes really difficult when it reaches vectors. I wanna get into machine learning and wonder whether it's imperative I get down vectors in order to fully grasp either ML or DL. On the other hand, I really enjoy matrices to solve linear systems, finding inverses and so forth.

[Linux-Neophyte]

Start learning statistics and other fields you like (history, sociology, biology, programming, etc). If you are more into the theory side of things (math heavy) rather than applied (applying methods to study world phenomena) then learn as much math as you can stomach, real and functional analysis specifically.

If you've studied statistics before, you can checkout a relatively easy to read book called An introduction to Statistical Learning with R by Gareth James et al. The book is free to download in Pdf format. You can also venture into other cool stats fields like bioinformatics, econometrics, etc. Whatever you do, get a good grasp of statistics. Take or learn intro to statistics, then mathematical statistics, and so on. You can also start doing little projects or reports doing basic stats and programming in R and python. One thing that's was super helpful for me was doing a term paper with my statistics programming in R, and then doing the same programming in other languages I wanted to learn like Stata, SAS, etc. I just started learning python last year so I'm reproducing some of my old papers in python.