Patrick Altmeyer, Author at Towards Data Science https://towardsdatascience.com Publish AI, ML & data-science insights to a global community of data professionals. Wed, 05 Mar 2025 12:46:08 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.1 https://towardsdatascience.com/wp-content/uploads/2025/02/cropped-Favicon-32x32.png Patrick Altmeyer, Author at Towards Data Science https://towardsdatascience.com 32 32 ECCCos from the Black Box https://towardsdatascience.com/ecccos-from-the-black-box-c4bd6ef20263/ Thu, 08 Feb 2024 00:00:06 +0000 https://towardsdatascience.com/ecccos-from-the-black-box-c4bd6ef20263/ Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals Counterfactual explanations offer an intuitive and straightforward way to explain opaque machine learning (ML) models. They work under the premise of perturbing inputs to achieve a desired change in the predicted output. If you have not heard about counterfactual explanations before, feel free to also check out my […]

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]]> Building a Conformal Chatbot in Julia https://towardsdatascience.com/building-a-conformal-chatbot-in-julia-1ed23363a280/ Wed, 05 Jul 2023 00:00:30 +0000 https://towardsdatascience.com/building-a-conformal-chatbot-in-julia-1ed23363a280/ Conformal Prediction, LLMs and HuggingFace – Part 1 Large Language Models (LLM) are all the buzz right now. They are used for a variety of tasks, including text classification, question answering, and text generation. In this tutorial, we will show how to conformalize a transformer language model for text classification using [ConformalPrediction.jl](https://juliatrustworthyai.github.io/ConformalPrediction.jl/dev/). 👀 At a […]

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]]> Prediction Intervals for any Regression Model https://towardsdatascience.com/prediction-intervals-for-any-regression-model-306930d5ad9a/ Mon, 12 Dec 2022 00:00:14 +0000 https://towardsdatascience.com/prediction-intervals-for-any-regression-model-306930d5ad9a/ Conformal Prediction Intervals for any Regression Model Conformal Prediction in Julia – Part 3 This is the third (and for now final) part of a series of posts that introduce Conformal Prediction in Julia using [[ConformalPrediction.jl](https://github.com/pat-alt/ConformalPrediction.jl)](https://github.com/pat-alt/ConformalPrediction.jl). The first post introduced Conformal Prediction for supervised classification tasks: we learned that conformal classifiers produce set-valued predictions that […]

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]]> How to Conformalize a Deep Image Classifier https://towardsdatascience.com/how-to-conformalize-a-deep-image-classifier-14ead4e1a5a0/ Mon, 05 Dec 2022 00:00:27 +0000 https://towardsdatascience.com/how-to-conformalize-a-deep-image-classifier-14ead4e1a5a0/ Conformal Prediction in Julia – Part 2 Deep Learning is popular and – for some tasks like image classification – remarkably powerful. But it is also well-known that Deep Neural Networks (DNN) can be unstable (Goodfellow, Shlens, and Szegedy 2014) and poorly calibrated. Conformal Prediction can be used to mitigate these pitfalls. In the first […]

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]]> Conformal Prediction in Julia 🟣🔴🟢 https://towardsdatascience.com/conformal-prediction-in-julia-351b81309e30/ Tue, 25 Oct 2022 00:00:39 +0000 https://towardsdatascience.com/conformal-prediction-in-julia-351b81309e30/ Conformal Prediction in Julia A first crucial step towards building trustworthy AI systems is to be transparent about predictive uncertainty. Model parameters are random variables and their values are estimated from noisy data. That inherent stochasticity feeds through to model predictions and should to be addressed, at the very least in order to avoid overconfidence […]

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]]> A new tool for explainable AI https://towardsdatascience.com/a-new-tool-for-explainable-ai-65834e757c28/ Wed, 20 Apr 2022 00:00:00 +0000 https://towardsdatascience.com/a-new-tool-for-explainable-ai-65834e757c28/ Explaining models trained in Julia, Python and R through counterfactuals

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]]> Go deep, but also … go Bayesian! https://towardsdatascience.com/go-deep-but-also-go-bayesian-ab25efa6f7b/ Fri, 18 Feb 2022 00:00:00 +0000 https://towardsdatascience.com/go-deep-but-also-go-bayesian-ab25efa6f7b/ Go deep, but also … go Bayesian! Deep learning has dominated AI research in recent years – but how much promise does it really hold? That is very much an ongoing and increasingly polarising debate that you can follow live on Twitter. On one side you have optimists like Ilya Sutskever, chief scientist of OpenAI, […]

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]]> Bayesian Logistic Regression https://towardsdatascience.com/bayesian-logistic-regression-53df017ba90f/ Mon, 15 Nov 2021 00:00:00 +0000 https://towardsdatascience.com/bayesian-logistic-regression-53df017ba90f/ From scratch in Julia language

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]]> Individual recourse for Black Box Models https://towardsdatascience.com/individual-recourse-for-black-box-models-5e9ed1e4b4cc/ Mon, 26 Apr 2021 00:00:00 +0000 https://towardsdatascience.com/individual-recourse-for-black-box-models-5e9ed1e4b4cc/ Model Interpretability Intuitively explained through a tale of cats and dogs "You cannot appeal to [algorithms]. They do not listen. Nor do they bend." – Cathy O’Neil In her popular book Weapons of Math Destruction Cathy O’Neil presents the example of public school teacher Sarah Wysocki, who lost her job after a teacher evaluation algorithm […]

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