Backpropagation Implementation: Neural Networks Learning From Theory To Action

We’ve focused on the math behind neural networks learning and proof of the backpropagation algorithm. Let’s face it, mathematical background … More

The Math Behind Neural Networks Learning with Backpropagation

Neural networks are one of the most powerful machine learning algorithm. However, its background might confuse brains because of complex … More

Sigmoid Function as Neural Network Activation Function

Sigmoid function (aka logistic function) is moslty picked up as activation function in neural networks. Because its derivative is easy to demonstrate. … More

Introduction to Neural Networks: A Mechanism Taking Lessons From The Past

Neural Networks inspired from human central nervous system. They are based on making mistakes and learning lessons from past errors. They … More

Exponential Smoothing: A Forecasting Approach Smoke Pleasure Triggered

Smoothing methods basically generalize the time series functions based on previous examples’ seasonal effects and trends. In this way, these methods … More