redmind 0.0.3

Package for building Machine learning models

RedMind

This is a python library made to help you build machine learning models.

Developed by Diego Velez 2022

Quickstart

import numpy as np
from redmind.layers import Dense, Sigmoid
from redmind.network import NeuralNetwork
import redmind.functions as fn

# Prepare data
xor = np.array([[0, 0],
                [0, 1],
                [1, 0],
                [1, 1]])

y = np.array([0, 1, 1, 0]).reshape(1,4)
x_test = xor.T

n_weights_1 = 10 # 3 neurons in the first layer
n_weights_2 = 1 # 1 neuron in the second layer (output)
nn = NeuralNetwork(layers=[
        Dense(n_weights_1, x_test.shape[0]),
        Sigmoid(),
        Dense(n_weights_2, n_weights_1),
        Sigmoid()
    ], cost_function=fn.mse, 
    grad_function=fn.mse_prime)
nn.set_verbose(True)

# Train
nn.train(X = x_test, Y = y, epochs = 1000, n_batches = 4, learning_rate=0.5)

# Predict
prediction_vector = nn.predict(np.array([[0],[0]]))

Go to samples folder for more samples

Objectives

• Classes definition and construction
• Forward propagation fully working
• Backward propagation working
• Train and predict fully working
• Add Optimization layers
• Add mini batch Gradient descent (through Dataloader)
• Add Gradient checking
• Support for multiple optimizers
• Learning rate decay
• Add early stoping support
• Add convolutional layers
• Add native pyplot support