
How to enter into ML? - alphagrep12345
I have a couple of years kf experience as SDE and I’m working towards my part time masters in ML. I find it very difficult to get into ML roles as almost no one hires inexperienced ML folks. How to break into it? Is doing a full time masters the only way?
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avi990
Hello, I have been in your shoes a couple of years ago. I was working as BI
engineer in Silicon Valley and realized the potential of ML and Data Science.
So I switched gears towards learning algorithms. I learned from logistic all
the way to Keras. But as you said, everything is theoretical. As I wasn't
working on the practical part of implementing, it has been difficult for me to
crack the interviews as most of the questions are related to the project. They
ask about your current project in ML and go deep dive in asking why you
haven't used a different algorithm, etc etc. I gave interviews and failed in
every one of them. But the good thing is that, I have learned through the
process and cracked one finally. it is still a mix of BI and ML. but no
complains as I don't have handson experience in ML. I suggest you to pick up
python, as almost every company asked me to code an algorithm. As you are
already an SDE, it shouldn't be of big concern. And the main reason is that,
python has vast libraries for data science. Go through the underlying
definitions of all ML algorithms. Pick a ML project which your company is
working and try to get as much exposure as possible. Trust me, the part-time
masters doesn't really matter in cracking a job. It all depends on how well
you explained the project, why you implemented a specific algorithm and not
the others, challenges in data analysis before implementing ML and of course,
coding interview. Good luck.

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rakeshpaul
Please give a try to [http://www.fast.ai](http://www.fast.ai) free courses on
practical machine learning. These courses had huge impact on people wanting to
enter into the world of machine learning like me.

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wpmoradi
Several ways to get noticed in the application process: * Go to Kaggle and
participate in some of their competitions. * Build an ML program from the
ground up to help build your portfolio (something like a dog door that only
opens to your dog). * Implement a paper from arxiv - try to understand what
the paper is about, then download the data set and implement the model they
are talking about and see if you get similar results. Then, write a blog post
about what you did....

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potbelly83
Why? What's this obsession with ML? There are tons of interesting problems in
the embedded/distributed systems/security spaces.

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Zofren
Maybe they're interested in it?

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CletusTSJY
It may be easier to get a position as a more general purpose engineer (full
stack or whatever you’re most comfortable in) with a team that has ML
engineers, and work your way into the role you want from there.

