Neural networks produce multiple outputs in multi-class classification problems. However, they do not have ability to produce exact outputs, they … More
Author: Sefik Serengil
Transfer Learning in Keras Using Inception V3
Machine learning researchers would like to share outcomes. They might spend a lot of time to construct a neural networks … More
Logarithm of Sigmoid As a Neural Networks Activation Function
Previously, we’ve reviewed sigmoid function as activation function for neural networks. Logarithm of sigmoid states it modified version. Unlike to … More
A Step by Step ID3 Decision Tree Example
Decision tree algorithms transfom raw data to rule based decision making trees. Herein, ID3 is one of the most common … More
How Random Forests Can Keep You From Decision Tree
Life cycle of a tree begins with a seed. Then seed grows and becomes a young plant. Young plant is … More
Softsign as a Neural Networks Activation Function
Activation functions play pivotal role in neural networks. As an alternative to hyperbolic tangent, softsign is an activation function for … More
Softmax as a Neural Networks Activation Function
In fact, convolutional neural networks popularize softmax so much as an activation function. However, softmax is not a traditional activation function. … More
Developers vs Mathematicians
Fermat’s last theorem has been waiting almost 350 years to be proven. Now, we can call it theorem but until 90s … More
Handwritten Digit Recognition Using CNN with Keras
Image recognition studies have reached incredible accuracy levels for the past several years. It is undeniable fact that deep learning has defeated … More
A Gentle Introduction to Convolutional Neural Networks
Convolutional neural networks (aka CNN and ConvNet) are modified version of traditional neural networks. These networks have wide and deep … More
