* Deleted greatest_common_divisor def from many files and instead imported the method from Maths folder
* Deleted greatest_common_divisor def from many files and instead imported the method from Maths folder, also fixed comments
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* Deleted greatest_common_divisor def from many files and instead imported the method from Maths folder, also fixed comments
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* In place of calculating the factorial several times we can run a loop k times to calculate the combination
for example:
5 C 3 = 5! / (3! * (5-3)! )
= (5*4*3*2*1)/[(3*2*1)*(2*1)]
=(5*4*3)/(3*2*1)
so running a loop k times will reduce the time complexity to O(k)
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* Replacing the generator with numpy vector operations from lu_decomposition.
* Revert "Replacing the generator with numpy vector operations from lu_decomposition."
This reverts commit ad217c6616.
* Added doctests.
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* ValueError: Number 22.2 must instead be a positive integer
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* Replacing the generator with numpy vector operations from lu_decomposition.
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* Added type annotation.
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* Fix: Issue 9588
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* Replacing the generator with numpy vector operations from lu_decomposition.
* Revert "Replacing the generator with numpy vector operations from lu_decomposition."
This reverts commit ad217c6616.
* Added type annotation.
* Replacing the generator with numpy vector operations from lu_decomposition.
* Revert "Replacing the generator with numpy vector operations from lu_decomposition."
This reverts commit ad217c6616.
* Added type annotation.
* Update fermat_little_theorem.py
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* Moved file relu.py from maths/ to neural_network/activation_functions
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* 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
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* Removed ciphers/rabin_miller.py as it is already there maths/miller_rabin.py
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* feat(maths): add function to perform calculation
- Add single function to calculate sum of two positive numbers
using bitwise operator
* docs: add wikipedia url as explanation
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* Update sum_of_two_positive_numbers_bitwise.py
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* Update arc_length.py
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* Add doctests to continued_fraction.py for 0 and neg nums
* Fix continued_fraction.py to work for negative nums
Fix continued_fraction.py to work for negative nums by replacing int() call with floor()
* Move comment in doctest
* 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
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* tanh function been added
* tanh function been added
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* ELU activation is added
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* Exponential_linear_unit activation is added
* Exponential_linear_unit activation is added
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* SiLU activation is added
* mish added
* mish activation is added
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* Changes on interquartile_range
* numpy removed from interquartile_range
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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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