Category
Advanced Modeling
This category will cover several advanced statistical modeling methods using R or Python, including time series analysis, machine learning, deep learning, forecasting, text mining, network analysis, and Bayesian regression.
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Advanced Modeling
6 years ago
‘How do neural nets learn?’ A step by step explanation using the H2O Deep Learning algorithm.
Shirin Glander
Advanced Modeling
Visualizing Data
6 years ago
Decision Trees and Random Forests in R
Michael Grogan
Advanced Modeling
6 years ago
neuralnet: Train and Test Neural Networks Using R
Michael Grogan
Advanced Modeling
6 years ago
Working with panel data in R: Fixed vs. Random Effects (plm)
Michael Grogan
Advanced Modeling
7 years ago
Understanding Titanic Dataset with H2O’s AutoML, DALEX, and lares library
Bernardo Lares
Advanced Modeling
7 years ago
K-fold cross-validation in Stan
Lionel Hertzog
Advanced Modeling
7 years ago
Automated Text Feature Engineering using textfeatures in R
Abdul Majed Raja
Advanced Modeling
7 years ago
Explaining Keras image classification models with LIME
Shirin Glander
Advanced Modeling
7 years ago
Image classification with keras in roughly 100 lines of code
Shirin Glander
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