Applying neural networks could be divided into two phases as learning and forecasting. Learning phase has high cost whereas forecasting … More
Author: Sefik Serengil
Building Neural Networks with Weka In Java
Building neural networks models and implementing learning consist of lots of math this might be boring. Herein, some tools help researchers to … More
Hyperbolic Tangent as Neural Network Activation Function
In neural networks, as an alternative to sigmoid function, hyperbolic tangent function could be used as activation function. When you … More
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
Image is everything
You might remember the advertisements of Sprite in 90’s. The brand has a motto; image is nothing, thirst is everything, … More
Netflix law
Nowadays, Netflix almost takes the place of traditional cable cast especially in United States. The company has 46M subscribers in US, and 79M … More
