K-nearest neighbors
The k-nearest neighbors (KNN) algorithm is a non-parametric algorithm that can be used for either classification or regression. Non-parametric means that it makes no assumption about the underlying data or its distribution. It is one of the simplest Machine Learning algorithms, and has applications in a variety of fields, ranging from the healthcare industry, to the finance industry. More info on wikipedia. Source code available on GitHub.

Multilayer perceptron 
A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs. An MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the next one. Except for the input nodes, each node is a neuron (or processing element) with a nonlinear activation function. MLP utilizes a supervised learning technique called backpropagation for training the network.MLP is a modification of the standard linear perceptron and can distinguish data that are not linearly separable. More info on wikipedia. Source code available on GitHub.

LSTM 
A powerful type of neural network designed to handle sequence dependence is called recurrent neural networks. The Long Short-Term Memory network or LSTM network is a type of recurrent neural network used in deep learning because very large architectures can be successfully trained. More info on wikipedia.

WTBS indicator
When To Buy and Sell technical indicator is based on CNN - Convolutional Neural Network. NN use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. Convolutional networks were inspired by biological processes in which the connectivity pattern between neurons is inspired by the organization of the animal visual cortex. More info on wikipedia. Source code available on GitHub.