Definition of Independent Variable An independent variable is a variable that is manipulated by the experimenter in a scientific study. It is typically one factor that is changed while all other factors are kept constant. What is an Independent Variable used for? An independent variable is a type of variable used in statistical models and…
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 Intuitive Intuitive: Intuitive is defined as easily understood or grasped. What are the key benefits of creating Intuitive processes? The key benefits of creating intuitive processes are manifold. Firstly, it allows for a more user-friendly experience, as users can quickly and easily understand what they need to do in order to complete the…
Definition of Interpretability Interpretability: Interpretability is a measure of how easily a model’s predictions can be explained to humans. Models that are easy to interpret are more likely to be trusted and used in decision-making processes. Why does Interpretability matter? Interpretability is an important factor in how effective data science and machine learning tools are….
Definition of Interactive Interactive: Interactive refers to a mode of data analysis that allows the user to make changes to the data and see the results immediately. This is in contrast to a more traditional mode of data analysis, where the user makes changes to a model and then observes the results. What are the…
Definition of Insights Insights: Insights are the findings or conclusions that are drawn from data. Insights can be used to make better business decisions, understand customer behavior, and track progress on strategic initiatives. What are the types of Insights a business or organization would hope to gain from analyzing data? Data-driven insights can be used…
Definition of Input Input: Input refers to the data that is given to a machine learning algorithm in order to learn from it. The input can be in a number of formats, including text, images, and videos. What are the most common types of Input given to machine learning algorithms? The most common types of…
Definition of Inferential Statistics Inferential Statistics: Inferential statistics are a type of statistics that are used to make estimations about populations based on samples. This is done by using the data from the sample to calculate a statistic, which is then used to make an inference about the population. What are Inferential Statistics used for?…
Definition of Inference Inference: Inference is the process of using known information to draw conclusions about something that is unknown. In data science, inference is often used to draw conclusions from data that has been collected. This can be used to identify trends or patterns in data, or to make predictions about future events. What…