- EDA stands for Exploratory Data Analysis. It is an approach to analyzing and summarizing data in order to gain a better understanding of the patterns, relationships, and trends that may exist within the data.
- EDA is an important first step in data analysis, as it helps to identify any outliers, missing data, or other issues that may need to be addressed before more advanced analysis can take place.
- EDA can be done using a variety of techniques, including statistical analysis, visualization, and data mining.
- The goal of EDA is to uncover insights and patterns in the data that can be used to inform further analysis or decision-making.
Data science is an interdisciplinary field that combines statistical and computational techniques with domain expertise to extract insights and knowledge from data. It involves using various statistical and machine learning methods to analyze, process, and interpret large and complex data sets, with the aim of discovering hidden patterns, trends, and relationships that can be used to inform decision-making and drive business outcomes. Data science is a broad field that encompasses various sub-disciplines, including data engineering, data visualization, machine learning, deep learning, natural language processing, and more. It involves working with data from various sources, such as structured data from databases and spreadsheets, unstructured data from social media and text documents, and semi-structured data from APIs and web services Data science has become an essential field in today's digital age, where...
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