The-Math-of-Intelligence

Implementation of Artificial Intelligence models without using any blackbox or libraries 😎

A high level API that implements common Machine Learning algorithms from scratch with only numpy as dependency.

Available Machine Learning Algorithms include:

• Linear Regression
• Logistic Regression
• Support Vector Machine
• KMeans
• Self Organizing Map
• The Perceptron
• Multi-Layer Perceptron (n_layers)
• Convolutional Neural Network

How to use

import numpy as np
from sklearn.linear_model import LinearRegression

X = np.array([[0, 0, 1], [0, 1, 0], [1, 0, 0], [1, 0, 1]])
y = np.array([[0], [0], [1], [1]])

clf = LinearRegression()
clf.fit(X, y)
y_pred = clf.predict(np.array([[1, 1, 0]]))

print('Prediction: {}'.format(y_pred))

Requirements

Installing numpy using the Python Package Manager pip

pip install numpy

Installing matplot using the Python Package Manager pip to visualize data

pip install matplotlib

Credits

Siraj Raval