
Ask HN: How to get some practical experience with ML? - colobas
I recently did my finished a ML course at my university and I&#x27;ve been also reading up a lot on the subject. However, I need to materialize what I&#x27;ve learned into some practical work, i.e., projects. My ultimate goal would be to become a ML engineer, but I feel like even to get an internship in the area I&#x27;d already need to have some projects to show.<p>What do you recommend? Project-oriented books&#x2F;tutorials?<p>Thanks!
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codelitt
One of our guys started a tutorial series on writing an AI to play the game,
DOOM. It assumes very little knowledge and is a fun exercise to do when taking
a break from some of the great courses posted here. It's no replacement for
the excellent course work, but it is fun.:
[https://www.codelitt.com/blog/doom-ai/](https://www.codelitt.com/blog/doom-
ai/)

My favourite course for grasping the foundations of the concepts was Andrew
NG's course (although it seems like you're beyond this now):
[https://www.coursera.org/learn/machine-
learning](https://www.coursera.org/learn/machine-learning)

I think the best way to learn, is to build things though. Have you checked out
the Kaggle challenges? [https://www.kaggle.com/](https://www.kaggle.com/)
Those will give you great practical skills.

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colobas
Thanks for the insight!

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deepaksurti
Have a look at:
[http://www.cs.cmu.edu/~10701/projects.html](http://www.cs.cmu.edu/~10701/projects.html)
for project ideas. Project A1, A2, B etc listed on the page. You can then
apply the toolkit you used in the ML course and solve these and make a
portfolio of your ML projects.

Kaggle could be another option.

Else a well defined problem that you may want to solve in a domain: example
graphics: See some papers here:
[http://www.cs.ubc.ca/~van/research/machlearn.html](http://www.cs.ubc.ca/~van/research/machlearn.html)
which you could again solve in software.

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colobas
thanks a lot for the tip!

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colobas
*I recently finished.

Sorry for the typo.

