EDA, data processing, cleaning and extensive geospatial analysis on a selenium based web crawled dataset
- Updated
Mar 9, 2022 - HTML
EDA, data processing, cleaning and extensive geospatial analysis on a selenium based web crawled dataset
This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)
Bayesian Hierarchical Clustering
Assignments on ML using Python.........
Hierarchical and K-Means Clustering in R and application to California housing data
Customers RFM Clustering (Market Segmentation based on Behavioral Approach)
Clustering analysis on the data from the World Happiness Report 2021.
GUI version of https://github.com/guglielmosanchini/ClustViz
Time Series Clustering using Hierarchical Clustering (Agglomerative and Divisive)
Apresentação: Cluster e segmentação de clientes
A library of implementations in the 'iads' directory, plus Jupyter notebooks for testing
Data Visualizations from my Master's thesis.
Classification Model of Potential Credit Card Customers
Clustering of properties in teheran based in price, area and room, additionaly prediction of the price.
Exploratory data analysis with hierarchical clustering on data from Rotten Tomatoes about Jake Gyllenhaal’s movies
Contains code to run and visualize techniques like Clustering, PCA, Generative Modeling on publicly available data.
Unsupervised Learning: Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.
To use dataset provided in https://worldhappiness.report for years 2008-2020 to create a machine learning algorithm that can predict one's happiness score based on the criterias given in the report. Furthermore, a website is created to showcase the machine learning algorithm and various plots.
This repository serves as a collection of my work and learning in machine learning while my internship in Cellual-Technologies, including algorithm explanations, data preprocessing workflows, and two projects.
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