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6 days ago · Exploratory Data Analysis (EDA) is a crucial step in the data science workflow, enabling data scientists to understand the underlying structure of their data, detect patterns, and generate insights. Traditional EDA methods often require writing extensive code, which can be time-consuming and complex.
- 16 min
Apr 3, 2021 · The Iris flower data set or Fisher’s Iris data set is one of the most famous multivariate data set used for testing various Machine Learning Algorithms. There are 3 duplicates, therefore...
- Pranshu Sharma
Explore and run machine learning code with Kaggle Notebooks | Using data from Iris Species
Dec 30, 2022 · Learn how to perform EDA on the Iris dataset using Python and pandas. See the statistics, visualizations, and correlation of the four features and three classes of flowers.
May 15, 2024 · The Iris dataset is one of the most well-known and commonly used datasets in the field of machine learning and statistics. In this article, we will explore the Iris dataset in deep and learn about its uses and applications.
- 16 min
Oct 9, 2019 · How to perform Data analysis and visualization on IRIS data set using Pandas, Matplotlib and Seaborn libraries of Python.
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Sep 7, 2019 · By Definition, Exploratory data Analysis is an approach to analysing data to summarise their main characteristics, often with visual techniques. It is always a good to explore and compare a...