algorithms_illuminated
libmaths
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algorithms_illuminated | libmaths | |
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1 | 3 | |
7 | 75 | |
- | - | |
1.8 | 0.0 | |
over 3 years ago | over 2 years ago | |
Python | Python | |
MIT License | MIT License |
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algorithms_illuminated
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How useful is knowledge of data structures and algorithms and how to learn them best?
I think it is important if you are building tools but less so for applying them. Most DS/DA tools abstract away all the implementation details where the type of knowledge from a typical DS&A course matters. For learning, I LOVE Tim Roughgarden's lectures and book series. For me, they hit a great balance between intuition and depth. His book only provides pseudo-code, but I've implemented all of the problems with test cases in Python if that would help (as have many others if you Google for it). https://github.com/andrewdoss/algorithms_illuminated
libmaths
What are some alternatives?
algoexpert-data-structures-algorithms - A collection of solutions for all problem statements on the AlgoExpert Coding Interview platform.
threeXYZgraphing - 3d xyz graphing using threejs
algorithms - Minimal examples of data structures and algorithms in Python
SymPy - A computer algebra system written in pure Python
coding-problems - Solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures
algorithms-python - Set of solutions of classic algorithmic problems written in Python
Basic-Algorithms - Basic algorithms and data structures written in different programming languages
pygraphblas - GraphBLAS for Python
TheAlgorithms - All Algorithms implemented in Python
fxpmath - A python library for fractional fixed-point (base 2) arithmetic and binary manipulation with Numpy compatibility.
communities - Library of community detection algorithms and visualization tools