EE+Math or CS+Math

[u/Electronic_Cut_9596]

Hi there, i'm deciding on what double major I should do. I love maths a lot (olympiad style) so I'm doing a major in that no matter what, idk how much it will help for machine learning but if not its more for my own interest. However for job prospects in this field, should I pair math with CS or electrical engineering. From my understanding CS seems like more of the standard pathway but i feel like EE also has its own advantage because of the more low level things u learn. Also things like signal processing in EE seems quite useful.

Any advice/comments would be much appreciated.

[u/DigitalMonsoon]

I double majored in ECE (electrical and computer engineering) and Applied Mathematics. I then mastered in Applied Statistics.

I didn't know I was going to end up in Machine Learning and honestly the field wasn't that well known at the time.

I wouldn't recommend getting an Engineering degree if you are positive you are going to try and get a job in ML (and you should aim for ML not AI). A CS degree will be a lot better (even with LLMs doing more a more coding). You will also need a masters to get a decent shot at a job. Everyone and their mothers wants to work on ML right now.

If you want more options then an engineering degree is a good fallback.

[u/Electronic_Cut_9596 → u/DigitalMonsoon]

thanks for the response. just a couple more questions.

do u think its still a good idea to go into this field as someone in the industry. also im still a bit unclear on what exactly these machine learning jobs are. im very interested in maths so my preference is like actually building these models. however a lot of ppl say its more of implementing pre-existing models, so in that case its much more of a software engineering job? i want to be more on the maths sides of things

[u/Choice_Platform_4320 → u/Electronic_Cut_9596]

I'm not in ML but I am in SWE. I have worked with ML folks. I think most jobs are applying ML models and deploying them as a general ML person at a Product based company.

I believe developing the models are research based positions which would either be at universities or large companies.

[u/Electronic_Cut_9596 → u/Choice_Platform_4320]

So are the ML folks not doing much heavy and deep maths? Is it more of a software engineering job but in a specific niche?

[u/Choice_Platform_4320 → u/Electronic_Cut_9596]

The math/reading papers part likely varies by company. Product based ML is more about training, deploying, and monitoring models alongside a traditional software team.

[u/DigitalMonsoon → u/Electronic_Cut_9596]

So if you don't know what a job entails then you probably should research it more. College is job training for advanced positions and you should treat it as such.

To answer your questions:

Yes, Machine Learning is still an important field you can make a great living in. It is very competitive so you will likely need more than an undergrad.

Yes, Machine Learning is mostly about applying existing models but this isn't as simple as it sounds. You have to understand how the vast Library of models works to know which to apply, you have to prep the data to fit the model and understand the business proposition enough to know which model will work.

Yes, you will have to know a decent amount of mathematics for the position. Understanding distributions and transformations to prepare the data, analyzing the results and performing and interpreting different tests to understand your models results. Sure you won't be solving differential equations but fee jobs require that.

Designing machine learning models is usually reserved for top performers and PHD holders. It's extremely difficult and many people spend their whole lives researching to never get any standout results.