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All Algorithms implemented in Python
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.vs | ||
analysis/compression_analysis | ||
arithmetic_analysis | ||
binary_tree | ||
boolean_algebra | ||
ciphers | ||
compression | ||
data_structures | ||
digital_image_processing | ||
dynamic_programming | ||
file_transfer_protocol | ||
graphs | ||
Graphs | ||
hashes | ||
linear_algebra_python | ||
machine_learning | ||
maths | ||
Maths | ||
matrix | ||
networking_flow | ||
neural_network | ||
other | ||
Project Euler/Problem 01 | ||
project_euler | ||
searches | ||
simple_client | ||
sorts | ||
strings | ||
traversals | ||
.gitignore | ||
.lgtm.yml | ||
.travis.yml | ||
License | ||
README.md |
The Algorithms - Python
All algorithms implemented in Python (for education)
These implementations are for learning purposes. They may be efficient than the implementations in the Python standard library.
Contribution Guidelines
- File name should be in camel case.
- Write proper documentation of the code.
- Avoid input methods as far as possible. Assign values to the variables statically. This will make the code easy to understand and algorithm can be traced easily.
- Add a corresponding explaination to Algorithms-Explanation (Optional but recommended).
- Avoid importing external libraries for basic algorithms.