funModeling: New site, logo and version ????
funModeling is focused on exploratory data analysis, data preparation and the evaluation of models. Check the latest functions and website here 🙂continue reading.
Author: Pablo Casas
Tips before migrating to a newer R version
A summary of common problems that my colleagues and I had when migrating R / packages to newer version.continue reading.
SPAM detection using fastai ULMFiT – Part 1: Language Model
Tutorial to fastai ULMFiT model for classification texts (and some of the theory behind it) 🤖📚continue reading.
How Auth0’s Data Team uses R and Python
Auth0 Data Team shares their tooling, from R to Python, their favourite open-souce libraries for data science and data engineering 🛠continue reading.
Automatic data types checking in predictive models
Given certain data, and we need to create models (xgboost, random forest, regression, etc). Each one of them has its constraints regarding data types. Errors are not clear, here’s a...continue reading.
Fast data exploration for predictive modeling
Before predictive model creation, we need to check/change numerical, categorical, NAs, one unique value and high cardinality variables. This new function will assist us in this task.continue reading.
How to use `recipes` package from `tidymodels` for one hot encoding ?
Quick introduction to `recipes` package, from the `tidymodels` family, based on one hot encoding. Useful to automatize some data preparation tasks.continue reading.
Jugando con las dimensiones: desde Clustering, PCA, t-SNE…. ¡hasta Carl Sagan!
Explora la intersección de conceptos como reducción de dimensiones, clustering, preparación de datos, PCA, HDBSCAN, k-NN, SOM, deep learning….y Carl Sagan!continue reading.
A gentle introduction to SHAP values in R
Opening the black-box in complex models: SHAP values. What are they and how to draw conclusions from them? With R code example!continue reading.
New discretization method: Recursive information gain ratio maximization
This method can discretize a variable taking into consideration the target variable, similar to what decision tree do but with gain ratio.continue reading.
Feature Selection using Genetic Algorithms in R
From a gentle introduction to a practical solution, this is a post about feature selection using genetic algorithms in R.continue reading.
How to apply a function to a matrix/tibble
How to apply a function to a matrix/tibblecontinue reading.
How to create a sequential model in Keras for R
This tutorial will introduce the Deep Learning classification task with Keras. With focus on one-hot encoding, layer shapes, train & model evaluation.continue reading.
Sample size and class balance on model performance
Analyzing the relationship between the sample size and how it impacts on the accuracy in a classification modelcontinue reading.
How to self-publish a book: Customizing Bookdown
Centered around Bookdown, we will review some non-standard customizations in order to self-publish a book.continue reading.
How to self-publish a book: A handy list of resources
tl;dr: A list of useful resources aimed to self-publish a book on Amazon using Bookdown.continue reading.
Exploratory Data Analysis in R (introduction)
Exploratory data analysis (EDA) the very first step in a data project. We will create a code-template to achieve this with one function.continue reading.
Tutorial instalaciĂłn R y RStudio
Este tutorial tiene como propósito hacer el set-up inicial para empezar a desarrollar modelos machine learning en increíble lenguaje R.continue reading.
Introduction to Machine Learning for non-developers
A brief introduction to machine learning using the intuition behind decision trees and random forest for non-developers.continue reading.
