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 a 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 a 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…
