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

# 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…

# 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…

# 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…

# 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…

# 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…

# 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…

# Leaky ReLU as an Neural Networks Activation Function

Convolutional neural networks make ReLU activation function so popular. Common alternatives such as sigmoid or tanh have upper limits to…

# Elegant Signatures with Elliptic Curve Cryptography

Elegance is the only beauty that never fades. This is an loving Audrey Hepburn quote. I struggle to adapt this…

# Moving Numbers To Upside Down: Extended Euclidean Algorithm

You might be familiar with the upside down if you watched Netflix series Stranger Things. Eleven shows the underside of…