PCA Insights is a data analysis project aimed at applying Principal Component Analysis (PCA) to high-dimensional datasets for dimensionality reduction, visualization, and exploration.
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Updated
Nov 26, 2024 - Jupyter Notebook
PCA Insights is a data analysis project aimed at applying Principal Component Analysis (PCA) to high-dimensional datasets for dimensionality reduction, visualization, and exploration.
Advanced Lando tooling to improve day to day work.
A data processing and analysis pipeline designed to handle various jobs related to data transformation, quality assessment, deduplication, and formatting.
Normalize data with interfaces.
Missing bridge for synccing keyboard events across applications
Log Transformation with Regular Expressions
🐧 Clustering analysis of Antarctic penguins using unsupervised learning (K-Means, t-SNE, elbow method) to explore species and sex-based groupings — with a plot twist!
Repo where different methods for price regression are used (supervised machine learning)
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Fast, scalable package for routine attribute standardization tasks.
Sprint 9, Task 1
PL: Wtyczka QGIS Algolytics do standaryzacji polskich danych adresowych i geokodowania EN: Algolytics QGIS plugin for Polish address standarization and geocoding
Deep learning system to standardize billing products with a product master
Schema.org extension for bicycle and parts schema
Repo where different multiclass supervised machine learning methods are used
Annotation driven library to help creating Modular Crypt Fromat algorithm outputs
Customer Segmentation
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