Data science is a field that uses statistical, mathematical, and computational techniques to analyze and interpret complex data. It combines elements of computer science, statistics, and domain expertise to extract insights and support decision-making.
Feature scaling is the process of normalizing or standardizing data. It’s crucial because many algorithms perform better and converge faster when features are on a similar scale.
Common types include bar charts, line graphs, histograms, scatter plots, pie charts, heat maps, and box plots. Each serves a specific purpose in effectively conveying insights.
Time series analysis involves analyzing data points collected over time to identify trends, patterns, or seasonal effects.