Definitions:
- Lambda Architecture: A design pattern that combines both batch and stream processing methods. Lambda architecture uses a batch layer for processing large volumes of data and a speed layer for processing real-time data. This approach provides a robust framework for handling big data, ensuring both accuracy and timeliness of data processing.
- Latency: The time delay between the initiation of a data transfer or process and the completion of that transfer or process. In digital and cloud computing, low latency is crucial for real-time applications, such as video streaming, online gaming, and financial trading systems. Minimising latency is a key goal in designing high-performance systems.
- Learning Rate: A hyperparameter in machine learning that controls how much the model's parameters are adjusted during each iteration of training. The learning rate determines the step size in the optimisation process. A high learning rate can lead to faster convergence but may overshoot the optimal solution, while a low learning rate can result in slower convergence but more accurate results.
- Linear Regression: A statistical method used in predictive modelling to determine the relationship between a dependent variable and one or more independent variables. Linear regression models the relationship as a linear equation, allowing for predictions and insights into how changes in the independent variables affect the dependent variable.
- Logistic Regression: A statistical method used for binary classification problems. Logistic regression models the probability that an event occurs by using a logistic function. It is widely used in machine learning and data science for tasks such as spam detection, credit scoring, and medical diagnosis.
- Long-Short Term Memory (LSTM): A type of recurrent neural network (RNN) architecture that is designed to learn long-term dependencies in sequential data. LSTMs are capable of remembering past information and using it to make predictions, making them particularly effective for tasks such as speech recognition, natural language processing, and time series forecasting.
- Load Balancing: The distribution of network or application traffic across multiple servers to ensure that no single server becomes overwhelmed. Load balancing helps to optimise resource usage, increase throughput, and reduce latency, enhancing the performance and reliability of applications and services.
- Load Testing: A type of software testing that determines the system’s behaviour under expected and peak load conditions. Load testing involves simulating multiple users or transactions to assess the system's performance, identify bottlenecks, and ensure that it can handle the expected load without degrading performance.
- Long Tail: A concept in business and economics that describes the retailing strategy of selling a large number of unique items in relatively small quantities. In the context of digital and e-commerce, the long tail refers to the ability to offer a wide variety of products, catering to niche markets and increasing overall sales.
- Low-Code Development: A software development approach that requires little to no coding to build applications and processes. Low-code platforms provide visual interfaces and pre-built components, enabling non-technical users to create and customise applications quickly and efficiently. This approach is particularly useful for rapid prototyping and agile development.
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