eda-on-different-datasets's Introduction

Exploratory Data Analysis (EDA) Repository

This repository contains various Exploratory Data Analysis (EDA) and Machine Learning projects performed on different datasets using Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn, and other relevant libraries.

Overview

Objective: Conducted EDA and Machine Learning analysis on diverse datasets to extract insights and build predictive models.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn, and more.

Projects

1. Student Dataset EDA

Description: Explored the Student dataset to analyze patterns and trends.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

2. US Honey Dataset EDA

Description: Analyzed the US Honey dataset to understand production trends.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

3. Bank Dataset (Logistic Regression)

Description: Implemented Logistic Regression on the Bank dataset for predictive analysis.
Tools Used: Python, Pandas, NumPy, Scikit-learn.

4. Country Dataset EDA

Description: Conducted EDA on the Country dataset to explore socio-economic indicators.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

5. Diabetes Dataset EDA

Description: Explored the Diabetes dataset to identify risk factors.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

6. Insurance Dataset EDA

Description: Analyzed the Insurance dataset to inform decision-making.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

7. Purchase Dataset EDA

Description: Conducted EDA on the Purchase dataset to optimize marketing strategies.
Tools Used: Python, Pandas, NumPy, Seaborn, Matplotlib.

8. Naive Bayes Classification on Iris Dataset

Description: Implemented Naive Bayes classification on the Iris dataset using Seaborn.
Tools Used: Python, Pandas, NumPy, Seaborn, Scikit-learn.

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