Machine Learning for Business Process Improvement
Expert-defined terms from the Professional Certificate in Business Process Management with Artificial Intelligence course at UK School of Management. Free to read, free to share, paired with a globally recognised certification pathway.
Activation Function #
a mathematical function that determines the output of a neural network, it introduces non-linearity to the model, allowing it to learn and represent more complex relationships between inputs and outputs. Related terms: Sigmoid, ReLU, Tanh.
Active Learning #
a subfield of machine learning that involves actively selecting the most informative samples for labeling, to achieve a certain level of accuracy with a limited number of labels. Related terms: Semi-supervised Learning, Transfer Learning.
Adversarial Attack #
a type of cyber attack that involves manipulating the input data to a machine learning model, to cause it to misbehave or produce incorrect results. Related terms: Adversarial Training, Robustness.
Adversarial Training #
a technique used to improve the robustness of a machine learning model, by training it on adversarial examples that are designed to mislead the model. Related terms: Adversarial Attack, Regularization.
Agent #
a software program that uses artificial intelligence to perform tasks autonomously, it can be used to automate business processes and improve efficiency. Related terms: Autonomous System, Bot.
Anomaly Detection #
a technique used to identify unusual patterns or outliers in a dataset, it can be used to detect fraud or errors in a business process. Related terms: Outlier Detection, Noise Reduction.
Application Programming Interface (API) #
a set of rules and protocols that allows different software systems to communicate with each other, it can be used to integrate machine learning models with business applications. Related terms: Software Development Kit (SDK), Web Service.
Artificial General Intelligence (AGI) #
a type of artificial intelligence that is capable of performing any intellectual task that a human can, it is a long-term goal of artificial intelligence research. Related terms: Narrow Intelligence, Superintelligence.
Artificial Intelligence (AI) #
a field of computer science that involves the development of intelligent machines that can perform tasks autonomously, it can be used to improve business processes and decision making. Related terms: Machine Learning, Deep Learning.
Artificial Neural Network (ANN) #
a type of machine learning model that is inspired by the structure and function of the human brain, it consists of layers of interconnected nodes or neurons. Related terms: Deep Learning, Convolutional Neural Network (CNN).
Association Rule Learning #
a type of unsupervised learning that involves discovering rules and patterns in a dataset, it can be used to identify relationships between different variables. Related terms: Decision Tree, Clustering.
Asynchronous Learning #
a type of learning that involves training a machine learning model on a dataset that is not available all at once, it can be used to improve the efficiency of the training process. Related terms: Online Learning, Streaming Data.
Attribute #
a characteristic or feature of a dataset, it can be used to describe a variable or field in a database. Related terms: Feature, Variable.
Audit Trail #
a record of all the actions and changes made to a system or process, it can be used to track and monitor the performance of a business process. Related terms: Logging, Monitoring.
Autonomous System #
a system that can operate independently without human intervention, it can be used to automate business processes and improve efficiency. Related terms: Agent, Robot.
Backpropagation #
a technique used to train artificial neural networks, it involves propagating the error backwards through the network to update the weights and biases. Related terms: Gradient Descent, Optimization.
Bagging #
a technique used to improve the stability and accuracy of a machine learning model, it involves training multiple models on different subsets of the data. Related terms: Boosting, Ensemble Learning.
Batch Learning #
a type of learning that involves training a machine learning model on a batch of data all at once, it can be used to improve the efficiency of the training process. Related terms: Online Learning, Streaming Data.
Bayesian Network #
a type of probabilistic model that represents the relationships between different variables using a directed graph, it can be used to model complex systems and processes. Related terms: Graphical Model, Probabilistic Graphical Model.
Bias #
Variance Tradeoff: a fundamental problem in machine learning that involves finding a balance between the bias and variance of a model, it can be used to improve the accuracy and robustness of a machine learning model. Related terms: Overfitting, Underfitting.
Big Data #
a term used to describe large and complex datasets that are difficult to process and analyze using traditional methods, it can be used to improve business intelligence and decision making. Related terms: Data Mining, Data Science.
Binary Classification #
a type of classification problem that involves predicting one of two classes or labels, it can be used to solve a wide range of problems in business and industry. Related terms: Multi-class Classification, Regression.
Boosting #
a technique used to improve the accuracy and robustness of a machine learning model, it involves training multiple models on different subsets of the data and combining their predictions. Related terms: Bagging, Ensemble Learning.
Business Intelligence #
a set of techniques and tools used to analyze and interpret data to inform business decisions, it can be used to improve performance and competitiveness. Related terms: Data Mining, Data Science.
Business Process Management (BPM) #
a discipline that involves the design, execution, and monitoring of