Tag

r

Working with Dataframes in Julia

An excerpt from Julia for Data Analysis by Bogumil Kaminski

This article dives into working with data in dataframes with Julia.

Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.

Vectorizing Your Code using Broadcasting

An excerpt from Julia for Data Analysis by Bogumil Kaminski

Many languages designed for doing data science provide ways to perform vectorized operations, which is also often called broadcasting. In Julia, broadcasting is also supported. In this article you will see how to use it.

Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.

Using Multiple Dispatch in Julia

An excerpt from Julia for Data Analysis by Bogumil Kaminski

This article shows you how to use Multiple Dispatch in Julia.

Read it if you’re a data scientist or anyone who works with lots of data, and if you’re interested in the Julia language.

Robust Machine Learning with ML Pipelines

From Data Analysis with Python and PySpark by Jonathan Rioux

This chapter covers using transformer and estimators to prepare data into ML features.

Big Data is Just a Lot of Small Data: using pandas UDF, part 2

From Data Analysis with Python and PySpark by Jonathan Rioux

This article covers

·         Using pandas Series UDF to accelerate column transformation compared to Python UDF.

·         Addressing the cold start of some UDF using Iterator of Series UDF.

Big Data is Just a Lot of Small Data: using pandas UDF

From Data Analysis with Python and PySpark by Jonathan Rioux

This article covers

·   Using pandas Series UDF to accelerate column transformation compared to Python UDF.

·   Addressing the cold start of some UDF using Iterator of Series UDF.

Your Data under a Different Lens: window functions

From Data Analysis with Python and PySpark by Jonathan Rioux

This article covers window functions and the kind of data transformation they enable.

Training an SVM model in R with mlr

Hefin I. Rhys teaches you how to train, tune, and cross-validate a Support Vector Machine model using RStudio and the awesome mlr machine learning package.

Getting started with graphs

From R in Action, Third Edition by Robert Kabacoff

This article dicusses graphs and graphic using the ggplot2 package

Free eBook: Exploring Machine learning with R and mlr

MiniEbook_Rhys_EMLR

Chapters selected by Hefin Ioan Rhys

© 2023 Manning — Design Credits