* feat: adding Apriori Algorithm
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* fix: doctest, typo
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* fix: type error, code refactore
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* fix: refactore code
* fix: doctest
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* fix: E501, B007
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* fix: err
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* fix: arg typ err
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* fix: typo
* fix: typo
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* Replace generate_candidates() with itertools.combinations()
* mypy
* Update apriori_algorithm.py
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* Conolidated two scripts reverse_letters.py and reverse_long_words.py into one because of similar functionality
* Added a new line to accomodate characters without going over 88 char limit
* fixed grammar to pass pre-commit
* Changed faulty test case entirely to pass pre commit
* fixed a test case which was wrong
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* Python mirror_formulae.py is added to the repository
* Changes done after reading readme.md
* Changes for running doctest on all platforms
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* Doctest whitespace error rectification to mirror_formulae.py
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* Python mirror_formulae.py is added to the repository
* Changes done after reading readme.md
* Changes for running doctest on all platforms
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* Moved file relu.py from maths/ to neural_network/activation_functions
* Renamed relu.py to rectified_linear_unit.py
* Renamed relu.py to rectified_linear_unit.py in DIRECTORY.md
* DRAFT: GitHub Actions: Test on Python 3.12
Repeats #8777
* #8777
Some of our dependencies will not be ready yet.
* Python 3.12: Disable qiskit and tensorflow algorithms
* updating DIRECTORY.md
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* Add type hints to k_nearest_neighbours.py
* Refactor k_nearest_neighbours.py into class
* Add documentation to k_nearest_neighbours.py
* Use heap-based priority queue for k_nearest_neighbours.py
* Delete knn_sklearn.py
* updating DIRECTORY.md
* Use optional args in k_nearest_neighbours.py for demo purposes
* Fix wrong function arg in k_nearest_neighbours.py
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* Move and reimplement convert_number_to_words.py
- Move convert_number_to_words.py from web_programming/ to conversions/
- Reimplement the algorithm from scratch because the logic was very
opaque and too heavily nested
- Add support for the Western numbering system (both short and long)
because the original implementation only supported the Indian
numbering system
- Add extensive doctests and error handling
* updating DIRECTORY.md
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* updating DIRECTORY.md
* fix(get-top-billionaires): Handle timestamp before epoch
* updating DIRECTORY.md
* revert(pyproject): Re-implement ignore lru_cache
* fix(age): Update age to current year
* fix(doctest): Make years since dynamic
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* Fix ruff errors
Renamed neural_network/input_data.py to neural_network/input_data.py_tf
because it should be left out of the directory for the following
reasons:
1. Its sole purpose is to be used by neural_network/gan.py_tf, which is
itself left out of the directory because of issues with TensorFlow.
2. It was taken directly from TensorFlow's codebase and is actually
already deprecated. If/when neural_network/gan.py_tf is eventually
re-added back to the directory, its implementation should be changed
to not use neural_network/input_data.py anyway.
* updating DIRECTORY.md
* Change input_data.py_tf file extension
Change input_data.py_tf file extension because algorithms-keeper bot is being picky about it
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* Input for user choose his Collatz sequence
Now the user can tell the algorithm what number he wants to run on the Collatz Sequence.
* updating DIRECTORY.md
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* Added file basic_orbital_capture
* updating DIRECTORY.md
* added second source
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* accepted changes
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* corrected spelling error
* Added file basic_orbital_capture
* added second source
* fixed spelling errors
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* applied changes
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* added doctest
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* removed redundant constnant
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* added scipy imports
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* added doctests to capture_radii and scipy const
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* finalizing file. Added tests
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* Reimplement polynomial_regression.py
Rename machine_learning/polymonial_regression.py to
machine_learning/polynomial_regression.py
Reimplement machine_learning/polynomial_regression.py using numpy
because the old original implementation was just a how-to on doing
polynomial regression using sklearn
Add detailed function documentation, doctests, and algorithm
explanation
* updating DIRECTORY.md
* Fix matrix formatting in docstrings
* Try to fix failing doctest
* Debugging failing doctest
* Fix failing doctest attempt 2
* Remove unnecessary return value descriptions in docstrings
* Readd placeholder doctest for main function
* Fix typo in algorithm description
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