Perceptron
References
CI/CD.yml code
# name of the workflow
name: Upload Python Package
#when to execute - when you push changes on "main" branch
on:
push:
branches:
- main
# - dev => add for more branches if needed
# what to execute - lists jobs
jobs:
deploy: # first job ,you can list more jobs as well
runs-on: ubuntu-latest # CREATE UBUNTU ENVIRONMENT
steps:
- uses: actions/checkout@v2
- name: Set up Python #sets up python
uses: actions/setup-python@v2
with:
python-version: '3.7' # python version needed
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install build
- name: Build package
run: python -m build
- name: Publish package
uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29
with:
user: __token__
password: ${{ secrets.PYPI_API_TOKEN }}
How to use package
from perceptron_package.perceptron_class import Perceptron
import pandas as pd
def prepare_data(df):
""" Used to separate dependent and independent features
Args:
df (pd.dataframe): pandas dataframe
Returns:
tuple: returns tuple of dependent & independent variables
"""
X = df.drop("y",axis=1)
y = df["y"]
return X,y
def main(data ,eta,epochs):
df = pd.DataFrame(data)
df # Shape = (4,3)
X,y = prepare_data(df)
model = Perceptron(eta=eta, epochs=epochs) # Creating object of class Perceptron
model.fit(X, y) # Weights in last epoch are considered as final weights for prediction
_ = model.total_loss() # last Epoch's Sum of Errors , '_' indicates dummy variable
if __name__ == '__main__': # define entry point of program execution
AND = {"x1":[0,0,1,1],
"x2":[0,1,0,1],
"y" :[0,0,0,1]
}
ETA = 0.3 # between 0 and 1
EPOCHS = 10
main(AND,ETA,EPOCHS)
Release files for Perceptron-RabiaWadhwa 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Perceptron-RabiaWadhwa-0.0.2.tar.gz | 5.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Perceptron_RabiaWadhwa-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.1 kB
Release files / Perceptron-RabiaWadhwa-0.0.2.tar.gz
| Download URL | Perceptron-RabiaWadhwa-0.0.2.tar.gz |
|---|---|
| Size | 5.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d23c917b6024d6d2a0f5eb440d64b1d1a5555e9b813c711e2a4a9479b83d0285
|
|
BLAKE2b-256 checksum How to use checksums |
51e46e406b46d2a7fdf8a12dedfa85529c8b09905cde32b589b318499296f48e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|
Release files / Perceptron_RabiaWadhwa-0.0.2-py3-none-any.whl
| Download URL | Perceptron_RabiaWadhwa-0.0.2-py3-none-any.whl |
|---|---|
| Size | 6.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
161f67cead4c5ec1ab1a54f584091f135ec35c1868907a860d4e7469b73ec9d4
|
|
BLAKE2b-256 checksum How to use checksums |
d7b2613b8f335315e35d86a2f0b1a0611c6506703e1341a7d56b6dc04afa46db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|