Definitions:
- Kanban: A visual system for managing workflow that helps teams to visualise their work, limit work in progress, and maximise efficiency. Kanban boards use cards to represent tasks and columns to represent different stages of the workflow. This method is widely used in agile project management and software development to improve productivity and collaboration.
- Kernel Methods: A set of algorithms for pattern analysis that use kernel functions to transform data into a high-dimensional space where it can be more easily separated. Kernel methods are used in machine learning and data science for tasks such as classification, regression, and clustering. The most well-known kernel method is the support vector machine (SVM).
- K-Means Clustering: An unsupervised machine learning algorithm used for clustering data into K distinct groups. K-means clustering partitions the data into K clusters based on the similarity of data points, with the goal of minimising the variance within each cluster. It is widely used in data mining, market segmentation, and image compression.
- K-Nearest Neighbours (KNN): A non-parametric, instance-based learning algorithm used for classification and regression. KNN classifies objects based on the majority vote of its K nearest neighbours in the feature space. It is a simple but effective algorithm that is commonly used in data science and machine learning for tasks such as recommendation systems and anomaly detection.
- Key Management Service (KMS): A cloud service that provides centralised control over cryptographic keys used for data encryption and decryption. KMS ensures the secure storage, management, and usage of encryption keys, enabling organisations to protect sensitive data in the cloud. It is a crucial component of cloud security and compliance.
- Key Performance Indicators (KPIs): Measurable values that demonstrate how effectively a company is achieving key business objectives. KPIs are used to evaluate the success of an organisation, team, or individual in achieving specific goals. In the context of digital and UX, KPIs can include metrics such as user engagement, conversion rates, and customer satisfaction.
- Knowledge Distillation: A technique for transferring knowledge from a large, complex model (teacher) to a smaller, simpler model (student). Knowledge distillation involves training the student model to mimic the output of the teacher model, resulting in a more efficient and compact model that retains much of the performance of the larger model. This is particularly useful in AI and machine learning for deploying models in resource-constrained environments.
- Knowledge Graph: A structured representation of facts, entities, and their relationships. Knowledge graphs are used to organise and connect data from various sources, enabling semantic search, recommendation systems, and advanced analytics. They are widely used in fields such as natural language processing, data integration, and AI.
- Kubernetes: An open-source platform designed to automate the deployment, scaling, and management of containerised applications. Kubernetes enables the orchestration of containers across clusters of hosts, providing high availability, load balancing, and scalability. It is widely used in cloud computing and DevOps to manage microservices and distributed systems.
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