What MACHINE LEARNING algorithms should an aspiring data scientist learn and practice more?
Data36 Data Science Podcast - En podcast af Tomi Mester
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I get way too many questions from aspiring data scientists regarding machine learning. Like what parts of machine learning learning they should learn more about to get a job. And I don't want to disappoint you -- but the thing is that when you get started as a junior, ninety five percent of your projects won't be about Machine Learning. At least, that's a rough average. So what parts of machine learning should you learn more about when preparing for your first job?
Well. None? :-)
Okay, that's not true. There are some parts that you'll have to know about. I'll talk more about that in this episode.
- Youtube version: https://youtu.be/yHfRQwOkhJY
- Original article format here: https://data36.com/machine-learning-algorithms-for-juniors/
LINKS MENTIONED IN THE EPISODE:
- https://data36.com/linear-regression-in-python-numpy-polyfit/
- https://data36.com/jds/
- http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
- Newsletter: https://data36.com/newsletter
- Free mini-course: https://data36.com/how-to-become-a-data-scientist/
Check my website: https://data36.com
Get access to more data science tutorials, join the inner circle: https://data36.com/inner-circle
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