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Its an implementation of perceptron and can create plots for logic gates

Project description

oneNeuron_pypi

oneNeuron_pypi

How to use this

  1. In the main file create DataFrame for any of the logic gate
  2. import Perceptron from oneNeuron.perceptron API
  3. import prepare_data,save_model and save_plot from utils.all_utils API
  4. There are loggong modules already present in the API's. So, paste the below code as it is in the start of main file
logging_str = "[%(asctime)s: %(levelname)s: %(module)s] %(message)s"
logs_dir = "logs"
os.makedirs(logs_dir, exist_ok=True)
logging.basicConfig(filename=os.path.join(logs_dir, "running_logs.log"),level=logging.INFO, format=logging_str
,filemode='a')
  1. The above logging code creates logs directory and do the logging in running_logs.log file
  2. Then train the model accordingly and include logging wherever needed in the main program
from oneNeuron.perceptron import Perceptron
## get X and y and then use below commands
model = Perceptron(eta=eta, epochs=epochs)
model.fit(X,y)

References -

Official Python Docs

github docs for github actions

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