A data-driven sales analytics project that combines descriptive and predictive analysis to uncover business insights, identify trends, and forecast future sales performance through an interactive dashboard.
A powerful Streamlit web app for interactive CSV data analysis with visualizations, statistical insights, correlation heatmaps, outlier detection, and data cleaning - no coding required.
Importing Boston dataset and describing the overview of the data using libraries such as Numpy, Pandas, Matplotlib and Seaborn. Analysing and creating various visualizations (Box plot, Scatter plot, Histogram). Examining the data structure, missing values and inconstencies to ensure data quality.
Car Price Prediction using Machine Learning with Python, Pandas, Seaborn, Matplotlib, and Scikit-learn. Includes data preprocessing, EDA, Linear Regression, model evaluation, and feature importance analysis.
In this project i have taken the dataset from scikit-learn and made a model to predicted the house values on the basics of some features.
Titanic Survival Prediction using Decision Tree Classifier | Data Science Internship Task 1
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