Sequential modeling is indeed done on Recurrent Neural Networks (RNNs). RNNs are a type of neural network architecture specifically designed to work with sequential data, such as time series or text data.
The correct term for the diagram used to view correlation is a "scatterplot matrix" or "scatterplot matrix diagram." A scatterplot matrix allows you to visualize the relationships between multiple variables in a dataset by plotting scatterplots of each variable against all other variables.
Weighted average is indeed used in forecasting. In forecasting, a weighted average is used to assign different weights or importance to different data points or periods based on their significance or relevance to the forecasted value.
Machine learning plays a crucial role in data science, particularly in the context of prediction.
The correct answer is "None of the mentioned." The characteristics listed do not accurately describe processed data.
The standard deviation is indeed a measure of spread for a random variable. It quantifies the amount of variation or dispersion in a set of data. A higher standard deviation indicates a greater spread of values, while a lower standard deviation suggests that the data points are closer to the mean.
The statement "Raw data should be processed only one time" is FALSE. Raw data often requires multiple processing steps before it is ready for analysis. The processing steps can include cleaning, transforming, aggregating, filtering, or performing other operations to ensure the data is accurate, consistent, and in a suitable format for analysis.
