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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...

Reproducibility in Data Science

Towards Data Science

Science as a pursuit has always had Reproducibility at its core. After all, if a claim is made about the physical world, and the evidence does not support such a claim, it doesn’t matter how much…

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…

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…

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.

Achieve Reproducibility in your Machine Learning Project with these Two Tools

Towards Data Science

In machine learning, since there is no such thing as the best model, you may need to train different models and try out different parameters until you find the model that gives the highest accuracy…

Reproducible Machine Learning Results By Default

Machine Learning Mastery

Last Updated on August 16, 2020 It is good practice to have reproducible outcomes in software projects. It might even be standard practice by now, I hope it is. You can take any developer off the stre...

Introducing the Machine Learning Reproducibility Scale

Towards Data Science

Reproducibility in machine learning is a recurring topic, brought up both in research and industry. Lots of opinions, but no easy way to quantify or provide a standard for it. The Reproducibility Scal...

On the value of reproducibility

Towards Data Science

We arrived at a point in the history of science in which we have formally defined the so-called reproducibility crisis, known as the ongoing tendency to fail to reproduce or replicate results of…

Machine Learning code reproducibility using versioning

Towards Data Science

Machine Learning systems are based on 3 main components: data, code and model. The three components are interrelated in many ways and using a dependency control system, we can ultimately achieve…

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...

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

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…

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…

12 Factors of reproducible Machine Learning in production

Towards AI

The last two decades have yielded us some great understandings of Software Development. A big part of that is due to the emergence of DevOps and its wide adoption throughout the industry. Leading…

Data Science's Reproducibility Crisis

Towards Data Science

Nearly every field in science is facing a reproducibility crisis. What does this mean in terms of data science, and how can we address it before it gets any worse?

Automate your Machine Learning experiments with MLflow

Better Programming

A brief guide to getting more done with less work Continue reading on Better Programming

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...

How to get started with ML Reproducibility Challenge 2020

Towards Data Science

Learn how you can help mitigate the deep learning Reproducibility crises and sharpen your skills at the same time, with the help of PyTorch Lightning Bolts research toolbox. The ability to reproduce…

4 Challenges of Reproducibility in the Machine Learning Model Deployment

Towards Data Science

In the pipeline of a Machine Learning model, there are a few environments that we consider — research environment, development environment… Continue reading on Towards Data Science

Code Reproducibility Crisis in Science And AI

Towards AI

Saving AI and scientific research requires we share more images generated by the author using OpenAI’s DALL-E 2 Modern science suffers from a reproducibility problem. Typically, the output of a scien...

The Machine Learning Reproducibility Crisis

Pete Warden's blog

Gosper Glider Gun I was recently chatting to a friend whose startup’s machine learning models were so disorganized it was causing serious problems as his team tried to build on each other’s work and s...

Reproducible Research in Computational Science

Simply Statistics

First of all, thanks to Rafa for scooping me with my own article . Not sure if that’s reverse scooping or recursive scooping or…. The latest issue of Science has a special section on Data Replication ...