Perceptron Neural Network with one layer

We are going to implement stochastic, batch and mini batch gradient descent using basic data science libraries.

How to run?

Note: Please use Python3

Install the requirements:

pip install -r requirements.txt

Run the following command to run the code:


For each gradient descent type, graphs for MSE per iteration will be stored in plots/ directory after running the code.

Directory Structure

  • – Entry level for the project
  • – Contains layer class for each layer
  • – Contains neural network class with added layers
  • plots/ – Contains plots for MSEs


  • We’ve divided data set in ration of train: test :: 8: 2.
  • We’re considering bias as a weight for a feature, instead of computing it individually. So, we’ve added 1.0 to the feature set along with the four feature. The weights for this data point will compensate for bias value.
  • Mini batch size = 12
  • Total epochs = 1000
  • Using sigmoid as activation functon with threshold = 0.5
  • Hyperparameters for mini-batch and stochastic:
    • t0 = 0.1
    • t1 = 5

Thank you ?


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