Because I often work with categorical data, I find myself making lots of quick, sorted counts of variables in a dataset. I find that this is a really common technique to get to know a dataset you’re working with; I’ve also noticed David Robinson do it often in ...

Functions and iteration Introduction Functions in R allow us to automate things, instead of copy-pasting code. 3 major advantages : Functions can have names, so it makes code easier to read If your requirements change, you only have one place ...

Machine Learning at the Boundary: There is nothing new in the fact that machine learning models can outperform traditional econometric models but I want to show as part of my research why and how some models make given predictions or in this instance classifications. I wanted to show the decision ...

Version 0.4.0 of nnetsauce, with fruits and breast cancer classification

Introduction Null and alternative hypothesis Hypothesis testing Different versions of the Student’s t-test How to compute Student’s t-test by hand? Scenario 1: Independent samples with 2 known variances Scenario 2: Independent samples with 2 equal but unknown variances Scenario 3: Independent samples with 2 unequal and unknown variances Scenario 4: Paired samples where the variance ...

Original article published in opendatascience.com In the last couple of years, data science has seen an immense influx in various industrial applications across the board. Today, we can see data science applied in health care, customer service, governments, cyber security, mechanical, aerospace, and other industrial applications. Among these, manufacturing ...

Together with Clara Bicalho (UC Berkeley) and Sisi Huang (WZB), I recently developed a web application that acts as a … Read More →

The video recording of my RStudio::conf talk, MLOPS for R with Azure Machine Learning, is now available for streaming thanks to the fine folks at RStudio. The talk begins with a general discussion of MLOps (Machine Learning Operations) and how it differs from DevOps as applied to traditional (non-ML-based) ...

A paper (and an introduction to the paper) in Nature this week seems to have made progress on the existence of indefinite predator-prey cyles. As in the lynx/hare dataset available on R. The paper is focusing on another pair, an invertebrate and its prey, an algae. For which the ...

I can’t quite remember when I came up with the idea for this one, but I have a feeling this was a 3AM idea. I know the title doesn’t tell you much. I’m not talking about a Kramer Vs. Kramer reboot. Stone Cold Steve Austin isn’t ...

Newman and Postman form a great team to test your REST API. I will give you a quick roundtrip through both tools and their interplay: define requests and tests, export them, and let them run with CLI and within Jenkins. Der Beitrag Testing REST APIs with Newman erschien zuerst auf ...

New business and financial analysts are finding R every day. Most of these new userRs (R users) are coming from a non-programming background. They have ample domain experience in functions like finance, marketing, and business, but their tool of choice...

Usually, the first step of every nonlinear regression analysis is to select the function \(f\), which best describes the phenomenon under study. The next step is to fit this function to the observed data, possibly by using some sort of nonlinear lea...

The Bayesian framework is powerful and allows for an incredible amount of flexibility and control over your analysis. That being said, newcomers often struggle with a lot of new concepts and tools and could benefit from some familiar grounding. And the p-value is a very familiar index (although paradoxically often ...

Usually, the first step of every nonlinear regression analysis is to select the function \(f\), which best describes the phenomenon under study. The next step is to fit this function to the observed data, possibly by using some sort of nonlinear least squares algorithms. These algorithms are iterative, in the ...