## Autoencoder

Autoencoder refers to an unsupervised learning technique that is often used in the context of dimensionality reduction of big data. It projects some data from a higher dimension to a lower dimension via linear...

Autoencoder refers to an unsupervised learning technique that is often used in the context of dimensionality reduction of big data. It projects some data from a higher dimension to a lower dimension via linear...

Sequence to sequence learning with neural networks is a very effective method for predictions of sequences. Applications using sequence data are often in natural language processing (NLP) like speech recognition or machine translation. One...

Dimensionality reduction techniques are methods to reduce the dimensionality of a modeling problem. This is very important when working with big data and high-dimensional data sets. Learning from this data is a very challenging...

Activation function refers to specific function used in a neural network node that is used to compute the output of this node given a specific node input. Computing this function has more impact recently...

ReLU Neural Network is a well known phrase that stands for the Rectified Linear Unit (ReLU) activation function used more recently during the training of neural networks and deep learning networks used with big...

Tanh stands for hyperbolic tangent function and it is often used as a non-linear activation function in machine learning algorithms when working with big data. The particular interesting property of this function is that...

GGPLOT2 tutorial refers to this short tutorial on using the ggplot2 package of the statistical computing with R tool in order to create simple plots of functions. A wide variety of machine learning algorithms...

Plot function refers to the idea of understanding a function better and is very useful to understand certain properties of it especially in the context of various machine learning algorithms that take advantage of...

Sequence models enable various sequence predictions that are inherent different to other more traditional predictive modeling techniques or supervised learning approaches. In contrast to mathematical sets often used, the ‘sequence‘ model imposes an explicit...

Probability measure is a measure of how likely a future ‘event’ is when analyzing big data with various models such as in statistical learning theory in general and as an example a Markov Chain...