Where Can I Find Helpful Resources for Data Science and Machine Learning?

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In summary, there are many helpful resources available for data science and machine learning, including online courses, tutorials, blogs, and forums. Some popular options include Coursera, Kaggle, DataCamp, and Reddit's r/datascience community. Additionally, there are numerous books, podcasts, and conferences dedicated to these topics. It is also beneficial to join data science and machine learning communities to connect with other professionals and stay updated on the latest developments. With the abundance of resources available, individuals can continuously expand their knowledge and skills in these fields.
  • #1
inducer27
How did you find PF?
Just did a search for best math help sites on Google
I've worked in digital media and finance. The former was at CNET and CBS Interactive and the latter was at a tech oriented hedge fund. I've always been an analyst, even when I managed teams of them. I recently went back to school to study data science part time. One reason I went back to school is my professional work has given me a much greater appreciation for the importance of understanding uncertainty. And that understanding needs to be built on a really large stack of mathematical knowledge. I don't mind putting in hard work on problems sets or proofs but sometimes I get stuck and grind my gears unproductively. Being able to come to a site like this and get 'unstuck' would be really appreciated.
 
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  • #2
Welcome to PF!

With respect to math, there's two good websites to checkout:
- Khan Academy math upto first year college (Calculus, Linear Algebra, Diff Equations and Stat)
- www.mathispower4u.com with similar catalogs of courses

These are the courses useful for Data Science and ML

There's a website:

https://towardsdatascience.com/

with a lot of good articles on Python and Data Science techniques.

Lastly, there's the 100 page ML book and the Hands-on ML Book with Python... that get right to the point of ML and Data Science techniques and algorithms.
 
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