Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
-
Updated
Feb 9, 2017 - HTML
Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
High Accuracy of NBA game outcome & team performance prediction and outstanding player detection.
Ergebnisse der Datenanalyse vom Feinstaub Hackathon 2018 der Stuttgarter Zeitung
Customer Segments - Machine Learning Nanodegree from Udacity
Analyzing spotify data with computers
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.
This repo contains code, a presentation, and a project report regarding suicide rates in the US from 1985 - 2015
This repo contains a regression analysis of crime rates in the Boston area.
A collection of projects where I worked on building anomaly detection pipelines. This rep covers code for EDA, outlier detection, and stock analysis.
University of Utah—MKTG 66420 | Taken: Fall 2020
Machine Learning for Data Science lecture at Freie University Berlin during WiSe21/22
Time series anomaly detection and change-point on the univariate (potentially multivariate case) for time series economic data from LA concerning unemployment
Демонстрация применения методов преобразования и очистки данных на примере данных резюме на HeadHunter
Данный проект направлен на применение различных методов по предобработке данных
Analysis of resumes from the site hh.ru.
Supporting site for the Pawsey 2023 summer internship showcase event
Supplementary materials for the Meta-survey on outlier and anomaly detection paper.
HH applicant data research, cleaning and outliers detecting
Add a description, image, and links to the outlier-detection topic page so that developers can more easily learn about it.
To associate your repository with the outlier-detection topic, visit your repo's landing page and select "manage topics."