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Got asked a ton of questions about Machine Learning!
I decided to build a short FAQ to help you move forward.
Here are my answers to the 10 most frequently asked questions about getting into Machine Learning:
I decided to build a short FAQ to help you move forward.
Here are my answers to the 10 most frequently asked questions about getting into Machine Learning:
Do I need Probabilities / Statistics / Linear Algebra to get started?All of these help tremendously, especially if you want to understand how the algorithms work.
But they aren't a hard requirement to start applying some of the algorithms.
How relevant is a Ph.D. or MS degree to get a job?Companies are currently asking for degrees to weed out people that apply to jobs prematurely.
But degrees aren't a requirement most of the time. Your skillset is the most important factor.
Since degrees don't matter, why some people get one?Degrees are going to set you apart. It's another signal that employers use to make a decision.
There are many good things that come with a degree, but you can replace a lot of it with relevant experience.
I think the field is too crowded.The demand is still disproportionally larger than the number of applicants.
There's also a large gap between the skills required and the experience of the applicants.
If you invest in your skillset it will be easy to set yourself apart.
I am ___ years old. Am I too old to get into the field?No.
Should I look into Kaggle competitions?Absolutely! Even if you don't care about competitions, Kaggle is an amazing source of problems that you can work on to build your skillset and portfolio.
Should I focus on theory before working with real datasets?I'd try to understand what different Machine Learning algorithms do before applying them.
You don't need to understand "how" algorithms work, but you should be able to understand what they do.
Should I learn R or Python?I'd focus on Python.
Yes, there are a lot of things you can do with R, but Python will get you to the same place.
Deep Learning libraries (TensorFlow and PyTorch) are all Python.
You can also use Python for a lot of different applications.
What's the difference between "Data Science" and "Machine Learning"?Data Science seems to be heavier on the "science" part: modeling, new algorithms, etc.
Machine Learning is less science and more about engineering and applications.
What's the most important thing I should do to get a job?Build a portfolio that helps you show off your skillset.
You can do this on your own. Go into Kaggle and pick some interesting projects and start building.
A solid portfolio will open most doors.
If you are looking to get started, here is a thread with some information to help you get on this right away: https://twitter.com/svpino/status/1302107301424369664?s=20
