Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
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Updated
Feb 9, 2017 - HTML
Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
Time series anomaly detection and change-point on the univariate (potentially multivariate case) for time series economic data from LA concerning unemployment
This solution performs Anomaly Detection with Statistical Modeling on Spark. The detection is based on Z-Score calculated on cpu usage data collected from servers.
Machine Learning for Data Science lecture at Freie University Berlin during WiSe21/22
University of Utah—MKTG 66420 | Taken: Fall 2020
Данный проект направлен на применение различных методов по предобработке данных
This repo contains a regression analysis of crime rates in the Boston area.
HH applicant data research, cleaning and outliers detecting
High Accuracy of NBA game outcome & team performance prediction and outstanding player detection.
Supporting site for the Pawsey 2023 summer internship showcase event
Analyzing spotify data with computers
Ergebnisse der Datenanalyse vom Feinstaub Hackathon 2018 der Stuttgarter Zeitung
This repo contains code, a presentation, and a project report regarding suicide rates in the US from 1985 - 2015
Customer Segments - Machine Learning Nanodegree from Udacity
Supplementary materials for the Meta-survey on outlier and anomaly detection paper.
Analysis of resumes from the site hh.ru.
A collection of projects where I worked on building anomaly detection pipelines. This rep covers code for EDA, outlier detection, and stock analysis.
Демонстрация применения методов преобразования и очистки данных на примере данных резюме на HeadHunter
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