A long short-term memory neural network is a type of RNN, capable of learning long-term dependencies. The difference between a classical RNN and an LSTM network is the architecture of its cell. Instead of having just one single layer, a LSTM cell has four: σ 1): forget gate σ 2): input gate tanh: tanh layer […]
A recurrent neural network (RNN) is a type of neural network which uses sequence data or time series data. The major difference between a RNN and other networks is the capability of storing information derived from previous outputs. The most simple example of a RNN consists of just one single neuron. The neuron receives an […]
While working with datasets, it is often times required to change the shape of it. For example, you have one long list with all the data in it. Each data value inside the list reflects a daily record. If you are interested in a weekly analysis, you need to transform it from a one dimensional […]
Gradient descent is an optimization algorithm for finding the maximum/minimum of some function. It is an iterative approach where you are calculating the slope of a derivative function to move step wise to the maximum/minimum value. The slope on this example is at 2. By decreasing/increasing x step wise and comparing the result with the […]