Random Initialization in Neural Networks

Neural networks requires to apply several state-of-the-art techniques such as choice of activation function, or network design to push their … More

How Vectorization Saves Life in Neural Networks

Developers tend to handle problems with conditional statements and loops. This is the number one topic of developers and data … More

A Step By Step Bitcoin Address Example

A money transfer transaction must include sender and receiver account information and transaction amount. On the other hand, a bitcoin … More

Convolutional Autoencoder: Clustering Images with Neural Networks

Previously, we’ve applied conventional autoencoder to handwritten digit database (MNIST). That approach was pretty. We can apply same model to … More

Autoencoder: Neural Networks For Unsupervised Learning

Neural networks are like swiss army knifes. They can solve both classification and regression problems. Surprisingly, they can also contribute … More

Handling Overfitting with Dropout in Neural Networks

Overfitting is trouble maker for neural networks. Designing too complex neural networks structure could cause overfitting. So, dropout is introduced to … More

IBM Data Summit 2018 Istanbul Notes

IBM organized a data summit on March 15 in this year. Motto of the organization is plan, manage and optimize. Both … More

Oracle Analytics Summit 2018 Istanbul

Oracle Analytics Summit is held in Istanbul on 2018 Mar, 07. I have been attending this summit since 2016. I … More

Solving Elliptic Curve Discrete Logarithm Problem

Elliptic curve cryptography is powerful. Calculating public key from known private key and base point can be handled easily. On … More

Counting Points on Elliptic Curves over Finite Field: Order of Elliptic Curve Group

ECDSA enables to produce signatures faster. Besides, its both signatures and keys are much smaller than adopted alternative options offering … More