Daniel J. TOTH – Medium

Daniel J. TOTH
in
Towards Data Science

Binary Classification: XGBoost Hyperparameter Tuning Scenarios by Non-exhaustive Grid Search and…

Practical example of balancing model performance and computational resource limitations — with code and visualization

10 min readAug 28, 2021

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Binary Classification: XGBoost Hyperparameter Tuning Scenarios by Non-exhaustive Grid Search and…

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Daniel J. TOTH
in
Analytics Vidhya

Multi seasonal time series analysis: decomposition and forecasting with Python

A practical example for analyzing a complex seasonal time series with 100,000+ data points by the Unobserved Components Model

10 min readJul 21, 2021

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Multi seasonal time series analysis: decomposition and forecasting with Python

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Daniel J. TOTH
in
Analytics Vidhya

Exploratory data analysis (EDA) of non-seasonal time series

Selected EDA tools for gaining insights

9 min readJun 21, 2021

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Exploratory data analysis (EDA) of non-seasonal time series

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Daniel J. TOTH

Predicting soil texture from laboratory analysis results of selected parameters and comparison of…

A data science project for justifying empirical observation in the lab

8 min readFeb 3, 2021

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Predicting soil texture from laboratory analysis results of selected parameters and comparison of…

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Daniel J. TOTH

Predicting soil texture from lab analysis results of selected parameters and comparison of models…

A data science project for justifying empirical observation in the lab

8 min readFeb 1, 2021

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Predicting soil texture from lab analysis results of selected parameters and comparison of models…

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Daniel J. TOTH

Predicting soil texture from lab analysis results of selected parameters and comparison of models…

A data science project for justifying empirical observation in the lab

4 min readJan 28, 2021

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Predicting soil texture from lab analysis results of selected parameters and comparison of models…

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Daniel J. TOTH

Daniel J. TOTH

Biochemical engineer, former environmental lab analyst with quality focus. I do my best to bring high quality content to data science learners/enthusiasts.

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