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Discover and read the best of Twitter Threads about #programming

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(1/5) I grew up in the Programming Languages research community and have recently begun attending Machine Learning conferences. One perspective that I don't see much in either community is that #MachineLearning is a form of #programming.
(2/5) PL/formal methods researchers tend to think of programs as engineered objects, and study abstractions/tools for principled engineering. But the big assumption here is that you can formalize your goals and the world in which your programs run. That's not always realistic.
(3/5) In contrast, #MachineLearning lets programs be "found" objects. "I don't have a full spec for my program and can't write the code myself, but here's some data on what it does. Discover it!" This is still #programming, albeit done inductively rather than deductively.
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High level #python #tutorial thread:
Python is a high level language that runs bytecode in its virtual machine.
Everything is an object.
It supports OOP up to multiple inheritance and functional programming.
Typing is polymorphic - duck typing is preferred
A Python script is a file with a name like name.py - we indent at four spaces (it matters), comments (after #) don't execute - and is typically written like:

def main(): # function
print("Hello world")

if __name__ == '__main__': # then entry point
main()
A module is a reusable script:

"""this is a docstring at the top of the module - gives help on the module"""

import this # do imports at the top

def main(): # main at top or bottom
"""functions get docstrings too"""

if __name__... always at the bottom, assumed from now on
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