## Unsupervised Machine Learning

Unsupervised Machine Learning is a type of learning where there is no labeled data. The objective of unsupervised learning is for the learning algorithm to find patterns by similarities or differences from the data. Unsupervised learning systems are often used

## Multi-Layer Perceptron Model

Multi-layer Perceptron model (MLP) is an artificial neural network with three or more hidden layers. It is a feed-forward neural network that uses back propagation technique for training the network. Multi-layer perceptron model is sometimes referred to as the deep

## Logistic Regression Algorithm

Logistic Regression is a classification supervised learning algorithm that is used to predict variables with dichotomous output. It is a statistical model that uses probabilistic measure to predict the likelihood of a specific outcome. Logistic regression algorithm uses the logistic

## Linear Regression Algorithm

Linear Regression is a statistical algorithm that has found its use in machine learning field. It is a supervised learning algorithm that finds the relationship between the input variables (independent variable/s) and an output variable (dependent variable). Linear regression is

## Random Forest Algorithm

Random Forest Algorithm is an ensemble machine learning algorithm which is an extension of Bootstrap Aggregation (Bagging) models constructed from multiple decision trees. Ensemble methods are learning models that aggregates multiple machine learning algorithms of similar or different types so

## Decision Tree Algorithm

Decision Tree Algorithm is a non-parametric supervised learning algorithm that uses decision rules to present problem space as a tree representation. It is used for both the classification and regression tasks. Decision Trees algorithm is one of the popular machine

## Naive Bayes Algorithm

Naive Bayes is a probabilistic machine learning algorithm that uses the Bayes’ Theorem and conditional probability theory with assumption of independence (naive) between features in making predictions. It is one of the oldest algorithm in the family of machine learning.

## Support Vector Machine Algorithm

Support Vector Machine is a supervised learning algorithm that works by separating data points using the hyper-plane. The hyper-plane forms the decision boundary between the different data points. Support Vector Machine is used for both classification and regression tasks but

## K-Nearest Neighbor Algorithm

K-Nearest Neighbor algorithm or commonly referred to as KNN or k-NN is a non-parametric supervised machine learning algorithms. It is one of the widely used machine learning algorithm because of its simplicity. By being non-parametric, KNN algorithm does not make