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Jan 14

Use R for prototyping a productivity app

Building OCR tools with the R-language — R can be used for numerous applications. Its extensive amount of libraries include even non-statistical tools, such as optical character recognition (OCR) which is handy for productivity apps, such as for the automation of classical accounting tasks, e.g. registering bills with their data in a central log. The use-case of…

Rstats

6 min read

Use R for prototyping a productivity app
Use R for prototyping a productivity app

Sep 10, 2021

Finger exercises on data – Multicollinearity and factor analysis

How does multicollinearity affect a toy model under laboratory circumstances and what can be done about it — Background Multicollinearity is a topic that every first-year student comes across, even before multiple regression appears on the curriculum. …

Data Science

4 min read

Finger exercises on data – Multicollinearity and factor analysis
Finger exercises on data – Multicollinearity and factor analysis

Published in Towards Data Science

·Apr 30, 2021

Forecasting at scale with Facebook Prophet — a case study on its merits & limitations

Domain knowledge remains a deciding factor in machine learning applications — Background Time series forecasting is usually a complex task because the structure of already univariate data often contains many unobserved factors. Standard models such as ARIMA, or filters, e.g. Kalman Filter are complex models that often need tweaking which requires a rigorous understanding of the underlying theory.

Time Series Forecasting

5 min read

Forecasting at scale with Facebook Prophet — a case study on its merits & limitations
Forecasting at scale with Facebook Prophet — a case study on its merits & limitations

Published in Nerd For Tech

·Apr 24, 2021

Sample size and time series models — A case study on ARIMA() processes.

Goals and contents ARIMA timeseries models are often taught in econometrics courses as part of the regular business science curriculum and are thus put to use by sometimes inexperienced data scientists. The intention of this case study is to understand the data generating process behind simple MA(1) models and illustrate weakness of the…

Towards Data Science

6 min read

Sample size and time series models — A case study on ARIMA() processes.
Sample size and time series models — A case study on ARIMA() processes.
Konrad Hoppe

Konrad Hoppe

applied AI / strategy consultant / aspiring XC rider on weekends // http://www.konrad-hoppe.com

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