SD
Definition of SD
SD: SD stands for standard deviation.
SD: SD stands for standard deviation.
Definition of Data Science Data Science: Data science is the study of data and the application of statistical analysis, machine learning, and other computational techniques to extract knowledge from data. What is Data Science used for? Data Science is a field that combines science, mathematics, and technology to analyze data and make predictions. It is…
Definition of Iterative Iterative: Iterative means “repeatedly doing something.” In data science, this usually refers to the process of repeatedly running a machine learning or deep learning algorithm on a dataset in order to improve the accuracy of the predictions made by the algorithm. When is an Iterative process used in Machine Learning or Data…
Definition of Data Analysis Data Analysis: Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of extracting useful information from it. What is a Data Analysis used for? Data analysis is an important process used to gain insights and understanding from data sets. It can be used to uncover…
Definition of Data Engineering Data Engineering: Data engineering is the process of extracting meaning from data and transforming it into a form that can be used by business analysts, managers, and other decision-makers. Data engineering involves creating models and tools to make data more accessible and useful. What is Data Engineering used for? Data engineering…
Definition of Universality Universality: Universality is the property of being applicable to a class of objects or phenomena. In data science, this means that a model or algorithm can be used to solve a problem for a wide range of data sets. This makes universality an important property for any data science toolkit.
Definition of Waterfall Chart Waterfall chart: A waterfall chart is a type of data visualization that shows how a starting value (in the y-axis) changes over time (in the x-axis) through a series of intermediary values. It’s often used to illustrate how different factors contribute to a final outcome.