Reproducibility in ML - Learn Data Science with Travis

Reproducibility-in-ML

Addressing ML’s Reproducibility Crisis

Towards Data Science

You’re probably aware that machine learning (ML) has a reproducibility problem. Hundreds of pre-prints and papers are published every week in the ML space but too many can’t be replicated or…

A Common Misconception About Model Reproducibility

Daily Dose of Data Science

Today I want to discuss something extremely important about ML model reproducibility. Imagine you trained an ML model, say a neural network. It gave a training accuracy of 95% and a test accuracy of 9...

Building Reproducible Machine Learning Pipelines

Towards Data Science

Reproducibility is the accountability required from businesses to further understand and trust the adoption of Machine Learning into our day-to-day lives. As Machine Learning becomes more…

How Reproducibility Crisis is Eating Away the Credibility of Machine Learning Technology?

Analytics Vidhya

Reproducibility of results has become a big challenge for Machine Learning models. We explore the challenges and possible solutions.

Reproducibility

PyTorch documentation

Completely reproducible results are not guaranteed across PyTorch releases, individual commits, or different platforms. Furthermore, results may not be reproducible between CPU and GPU executions, eve...

Reproducible ML: Maybe you shouldn’t be using Sklearn’s train_test_split

Towards Data Science

Photo by Jason Dent on Unsplash Reproducibility is critical for robust data science — after all, it is a science. But reproducibility in ML can be surprisingly difficult: The behaviour of your model d...

On Reproducibility

Towards Data Science

Reproducibility is important to science. A scientific result isn’t considered confirmed until multiple studies have reached the same conclusion. Also, new work is more efficient if it can build on…

Wrapping up the Papers with Code ML Reproducibility Challenge — Spring 2021

Towards Data Science

Data Science Reproducibility is one of the core reasons DagsHub was established, and we’re constantly developing new tools and integration to support a fully reproducible workflow. This is why we’re…

Reproducible Machine Learning

Towards Data Science

The NeurIPS (Neural Information Processing Systems) 2019 conference marked the third year of their annual reproducibility challenge and the first time with a reproducibility chair in their program…

When LLMs Roll the Dice — the Reproducability puzzle

Level Up Coding

(Un)fortunately, the output from LLMs is not always reproducible. Chat Completions are non-deterministic by default, which means model outputs may differ from request to request. But why is that and h...

Patterns for Reproducing Machine Learning Features

Towards Data Science

How to reproduce flows in machine learning applications through reproducible features Continue reading on Towards Data Science

Asymptotics of Reproducibility

Simply Statistics

Every once in a while, I see a tweet or post that asks whether one should use tool X or software Y in order to “make their data analysis reproducible”. I think this is a reasonable question because, i...