* CONTRIBUTING.md: What is an Algorithm?
We are seeing too many _how-to examples_ for using existing Python packages so we should define what we want algorithm contributions to be.
* updating DIRECTORY.md
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
* Rename math/add.py to maths/add.py
* fixup! Format Python code with psf/black push
* Fix sum to add
* updating DIRECTORY.md
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: John Law <johnlaw.po@gmail.com>
* Text exception conditions
These are ValueErrors, not AttributeErrors.
* fixup! Format Python code with psf/black push
* Update perceptron.py
* Update perceptron.py
* Update perceptron.py
* Revert the test
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* Create Python/quantum/README.md
Started at #1831
* fixup! Format Python code with psf/black push
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* With all suggested changes ✅
possibly covered all the recommended guidelines
* Updated with both slow and faster algorithms
possibally covered all the recomendations
* removed the time comparision part!
* Update data_structures/stacks/next_greater_element.py
Co-Authored-By: Christian Clauss <cclauss@me.com>
* Update data_structures/stacks/next_greater_element.py
Co-Authored-By: Christian Clauss <cclauss@me.com>
* Update data_structures/stacks/next_greater_element.py
Co-Authored-By: Christian Clauss <cclauss@me.com>
* Update data_structures/stacks/next_greater_element.py
Co-Authored-By: Christian Clauss <cclauss@me.com>
* Add benchmark using timeit
https://docs.python.org/3/library/timeit.html
The performance delta between these two implementation is quite small...
```
next_greatest_element_slow(): 1.843442126
next_greatest_element(): 1.828941414
```
* Optimize slow() to create fast() - Three algorithms in the race
Three algorithms in the race
* Use a bigger test array with floats, negatives, zero
* Setup import next_greatest_element_fast
Co-authored-by: Christian Clauss <cclauss@me.com>
* Fix rehashing function will not call insert_data function
* Fix typo
* Update loop syntax instead of allocating a list
Co-Authored-By: Christian Clauss <cclauss@me.com>
Co-authored-by: Christian Clauss <cclauss@me.com>
* Add Monte Carlo estimation of PI
* Add type annotations for Monte Carlo estimation of PI
* Compare the PI estimate to PI from the math lib
* accuracy -> error
* Update pi_monte_carlo_estimation.py
Co-authored-by: John Law <johnlaw.po@gmail.com>
* autoblack: actions/checkout@v1 # Use v1, NOT v2
* fixup! Format Python code with psf/black push
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* Added Random Forest Regressor
* Updated file to standard
* Added Random Forest Classifier (Iris dataset) and a Confusion Matrix for result visualization
* spelling corrections
* review
* improved documentation, removed redundant variables, added testing
* added type hint
* camel case to snake case
* spelling fix
* review
* python --> Python # it is a brand name, not a snake
* explicit cast to int
* spaces in int list
* "!= None" to "is not None"
* Update comb_sort.py
* various spelling corrections in documentation & several variables naming conventions fix
* + char in file name
* import dependency - bug fix
Co-authored-by: John Law <johnlaw.po@gmail.com>
* Added Bilateral filter
* Added Bilateral filter
* changed types of varS and varI
* formatted with black
* added type hints
* changed variable names
* Update bilateral_filter.py
* Drop transitory variables, add parse_args()
Co-authored-by: vinayak <itssvinayak@gmail.com>
Co-authored-by: Christian Clauss <cclauss@me.com>
* estimate area under a curve defined by non-negative real-valued continuous function within a continuous interval using monte-carlo
* run black; update comments
* Use f”strings” and drop unnecessary returns
Co-authored-by: Christian Clauss <cclauss@me.com>
* Travis CI: Upgrade to Python 3.8
* updating DIRECTORY.md
* Tensorflow is not yet compatible with Python 3.8
* Disable k_means_clustering_tensorflow.py
* updating DIRECTORY.md
* Disable gan.py
* updating DIRECTORY.md
* Disable input_data.py
* updating DIRECTORY.md
* pip install a current version of six
* add example to estimate area under line using montecarlo
* separate estimate func and print statements
* use mean from stats package
* avoid creating extra variable
* min_value: float=0.0, max_value: float=1.0
* Update montecarlo.py
* Update montecarlo.py
* Rename montecarlo.py to monte_carlo.py
* Update monte_carlo.py
Co-authored-by: Christian Clauss <cclauss@me.com>
