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More importantly social media is bad for your mental health. It hits the brain in many of the same ways as the 'news' and those intentionally boring phone games. It causes dopamine dysregulation which leads to a dependency. Consider the anxiety you feel if you need to go to the bathroom and cannot find your phone. This dopamine dysregulation destroys your mood and motivation.

Being social is a good thing. However companies have figured out they need addictive properties in order to be successful. I previously worked on optimizing companies for user engagement and the addictive properties naturally fall out of the process. If social media satiates your desires you will actually use them less. Think about it; why are your keys always in the last place you look? Because once you find them you stop looking. If you want to keep people on your site you hide their keys. People love a challenge and will be even happier when they find them.

It's particularly bad with modern (low information) news media. I'm a compulsive news junkie* so I have to avoid the news in order to get anything done. I quit facebook and google over their insistence on pushing 'news'. It's junk food for the brain. It's low information and only gives an illusion of being informed. E.g. the recent election.

* Note: I consider HN to be social 'media' news and I am aware that I'm here 'chipping'. I do so intentionally in effort to avoid fettishising vices. Plus HN is as close as I get to an online group of peers. I only use HN after self-flagellating while repeatedly muttering "the flesh is weak".


"Introdocution to Statistical Learning" by Trevor Hastie et al. [1] They have a free online class through Stanford [2] Sign in to their system and you can take the archived version for free.

ISL is an excellent, free book, introducing you to ML, you can go deeper, but, to me this is where I wish I'd started. I am taking the Data Science track at Coursera (on Practical Machine Learning now) and I am kicking myself that I didn't start with ISL instead.

Now, I know you specifically asked about Python, but the concepts are bigger than the implementation. All of these techniques are available in Python's ML stack, scikit-learn, NumPy, pandas, etc. I don't know of the equivalent of ISL for Python, but if you learn the concepts and you're a programmer of any worth, you will be able to move from R to Python. Maybe take/read ISL, but do the labs in Python, that might be a fun way to go.

Lastly, to go along with ISL, "Elements of Statistical Learning" also by Hastie et al is available for free to dive deeper [3]

[1] -- http://www-bcf.usc.edu/~gareth/ISL/

[2] -- https://lagunita.stanford.edu/courses/HumanitiesandScience/S...

[3] -- http://statweb.stanford.edu/~tibs/ElemStatLearn/


I think it's good to note, as Derek does, the distinction between "2 cents' worth" and larger changes that do require senior input - otherwise you're just being the manager that the team create ducks for [1].

This is where coaching skills as a manager can prove useful. If you feel there are some minor changes that could be an improvement, but don't want to impose your will/opinion, coaching ('ask') can be a better response than managing ('tell').

For example, you might ask "If you had to improve anything, what would you change?" It's an open-ended question that will encourage your team member to think. They can reply "Nothing" if they're confident in the final solution, or they may propose some tweaks they weren't fully happy with - "I'm not sure if that's the right shade of blue" or "I think that's the right call to action, but maybe we could get another opinion". If those are reasonable improvements, empower them to implement the additional change; if you disagree with the extras they raise, tell them you consider the version they proposed to be superior, which empowers their original decision.

Just don't be the manager who expects a detailed response and change every time ... then you're right back to where you started.

[1] See point 5 https://blog.codinghorror.com/new-programming-jargon/


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