Algorithms

Fuzzy logic is a heuristic approach that allows for more advanced decision-tree processing and better integration with rules-based programming.

Architecture of a Fuzzy Logic System. Source: ResearchGate

Support Vector Machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.

Support Vector Machine (SVM). Source: OpenClipArt

Neural networks are a subset of machine learning and are at the heart of deep learning algorithms. The name/structure is inspired by the human brain copying the process that biological neurons/nodes signal to one another.

Deep neural network. Source: IBM

Convolutional Neural Networks (R-CNN) is an object detection algorithm that first segments the image to find potential relevant bounding boxes and then run the detection algorithm to find most probable objects in those bounding boxes.

Convolutional Neural Networks. Source: CS231n

Recurrent neural networks (RNNs) is a type of artificial neural network which uses sequential data or time series data.

Recurrent Neural Networks. Source: Slideteam

Multilayer Perceptrons (MLPs) is multi-layer neural networks composed of multiple layers of perceptrons with a threshold activation.

Multilayer Perceptrons. Source: DeepAI

Random forest is a commonly-used machine learning algorithm, which combines the output of multiple decision trees to reach a single result. A decision tree in a forest cannot be pruned for sampling and therefore, prediction selection. Its ease of use and flexibility have fueled its adoption, as it handles both classification and regression problems.

Random forest. Source: wikimedia

Decision trees are tree-structured models for classification and regression.

Decision Trees. Source: CMU

Naive Bayes is a machine learning algorithm that is used solved calssification problems. It's based on applying Bayes' theorem with strong independence assumptions between the features.

Bayes' theorem. Source: mathisfun