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The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.
Used Python 3.9, used packageUsed NASA’s MAST Archive for Space Telescopes data to provide the AI with accurate results to determine if the planet is an exoplanet.
¡Bienvenido al repositorio de proyectos de análisis estadístico con Python! Este repositorio contiene una serie de proyectos prácticos que cubren diversos aspectos del análisis estadístico utilizando el lenguaje de programación Python.
Examined factors influencing demand for micro-mobility shared electric cycles Performed exploratory analysis and hypothesis testing, revealing the distinct influence of weather-season association on hourly counts
Project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and faces lower risk by tempering potential losses when the market is down.
"This repository hosts an implementation of the Singular Value Decomposition (SVD) algorithm tailored for data mining tasks. SVD is utilized for efficient dimensionality reduction, aiding in the extraction of key patterns and features from large and complex datasets."
This project involved Data Engineering and Data Analysis where I designed the tables to hold data from 6 CSV files, imported the CSVs into a SQL database using PostgreSQL and wrote SQL queries to answer the given questions. A bonus analysis included creating some charts to analyze employee salary data.
"This repository contains an implementation of the Principal Component Analysis (PCA) algorithm, which is one of the key techniques used for dimensionality reduction in data mining and machine learning."