data-science-live-book 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 :)
data science 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.
fastai SPAM detection using fastai ULMFiT - Part 1: Language Model Tutorial to fastai ULMFiT model for classification texts (and some of the theory behind it) 🤖📚
Python 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 🛠
data cleaning 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 new function to speed up model creation.
data preparation 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.
machine learning 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.
clustering Jugando con las dimensiones: desde Clustering, PCA, t-SNE.... ¡hasta Carl Sagan! 👉 Actualización! 7/4/20 La nueva versión de este post con mejoras y comentarios sobre UMAP, acá: https://escueladedatosvivos.ai/blog/204650/jugando-con-las-dimensiones-clustering-pca-tsne-carl-sagan Jugando con las dimensiones ¡Hola! Este post es un experimento
libro-vivo-ciencia-datos Lanzamiento! Libro Vivo de Ciencia de Datos 📗 (open-source) Finalmente disponible la versión en español del _Data Science Live Book_! El libro se abre sin barreras idiomáticas ante las personas de habla-hispana con ganas de aprender 👨🎓👩🎓. Esta publicación es una edición revisada tanto en gramática como en aspectos técnicos de la versión en inglés.
shap 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!
data preparation 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.
R 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.
tibble How to apply a function to a matrix/tibble Scenario: we got a table of id-value, and a matrix/tibble that contains the id, and we need the labels. It may be useful when predicting the Key (or Ids) of in a
deep-learning 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.
machine learning 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 model
bookdown How to self publish a book: customizing Bookdown tl;dr: This post is related to How to self-publish a book: A handy list of resources. It's centered around Bookdown and some non-standard customizations I found useful to create the Data Science
bookdown 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.
exploratory data analysis 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.
rstats Tutorial instalación R y RStudio Este tutorial tiene como propósito hacer el set-up inicial para empezar a desarrollar modelos machine learning en increíble lenguaje R.
machine learning Introduction to Machine Learning for non-developers About Machine Learning We all know that machine learning is about handling data, but it also can be seen as: The art of finding order in data by browsing its inner information. Some
learning "I hate math!" - Education and Artificial Intelligence to find a meaning in what we do Well, what you hate is the way that math was taught to you. That soup of equations, abstractions, and solutions to problems that we don’t know, It's hard to enjoy the things
data-science-live-book Data Science Live Book available at Amazon! Hi there! tl;dr: The Data Science Live Book is now available at Amazon! Kindle & Paperback versions! 🚀 👉 See at Amazon 📗! Link to the black & white version, also available on full-color. It
rstats Exploratory Data Analysis & Data Preparation with 'funModeling' funModeling quick-start This package contains a set of functions related to exploratory data analysis, data preparation, and model performance. It is used by people coming from business, research, and teaching (professors and students)
rstats Data discretization made easy with funModeling tl;dr: Convert numerical variables into categorical, as it is shown in the next image. ⏳ Reading time ~ 6 min. Let's start! The package funModeling (from version > 1.6.6) introduces two functions—
