Exploratory Data Analysis (EDA)
Exploratory Data Analysis is a critical step in the data analysis process that involves analyzing and visualizing data to understand its key characteristics, uncover patterns, and identify potential relationships between variables. In this session, participants will learn about the principles and techniques of EDA and how to apply them to real-world datasets.Participants will explore methods for summarizing and visualizing data, such as histograms, box plots, and scatter plots. They will also learn how to identify outliers, missing values, and other data issues that may impact the analysis.Through hands-on exercises and case studies, participants will gain practical experience in conducting EDA and interpreting the results. By the end of the session, participants will have a solid understanding of EDA principles and how to apply them to gain valuable insights from data.
Related Conference of Exploratory Data Analysis (EDA)
10th World Congress on Computer Science, Machine Learning and Big Data
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11th International Conference on Data Science and Machine Learning Applications
Exploratory Data Analysis (EDA) Conference Speakers
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