Nonlinear: Nonlinearity means that the output of a system is not proportional to the input. In data science, this can often manifest as curved lines when graphing data points, rather than a straight line. Nonlinear systems can be more difficult to model and predict future outcomes.
Definition of Reinforcement Learning Reinforcement Learning: Reinforcement learning is a type of machine learning that allows machines to learn by trial and error. In reinforcement learning, the machine is given feedback after each trial, which allows it to learn which actions lead to positive outcomes. Reinforcement learning is often used to train robots or other…
Definition of Eigenvector Eigenvector: An eigenvector is a particular type of vector that has a special property: it’s multiplied by a certain matrix (the “eigenvalue matrix”) in such a way that the result is always the same. What is an Eigenvector used for? An Eigenvector is a special type of vector used in linear algebra…
Definition of Data Preparation Data preparation: Data preparation is the process of getting data ready for analysis. This often includes cleaning up the data, removing outliers, and transforming it into a form that is suitable for the analysis that will be performed. Why is a Data Preparation process used? What is it good for? Data…
Definition of Quartile Quartile: A quartile is a statistic that divides a data set into four equal parts. The first quartile is the lowest 25% of the data, the second quartile is the lower 50% of the data, the third quartile is the upper 50% of the data, and the fourth quartile is the highest…
Definition of Upstream Upstream: Upstream and Downstream are terms used in data science to describe the flow of data or what order events occur. Data is processed and becomes more refined as it moves through the various processes. Upstream is closer to the source. When discussing a specific process step, Downstream is a term that…