corpus.blog
41554 blogs · [ { "id": "01a087c0-12e3-73ec-b234-abce0bb738f5", "title": "Agent Token Costs Are System Costs: Evaluate Your Agentic Tooling End-to-End", "url": "https://www.peterbaumgartner.com/blog/e2e-evals-agents/", "published_at": "2026-06-13T14:29:16+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0cb37029", "title": "Reporting With Quarto", "url": "https://www.peterbaumgartner.com/blog/reporting-with-quarto/", "published_at": "2024-02-05T12:51:34+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0cd83522", "title": "Wrapping a Rust Crate in a Python Package", "url": "https://www.peterbaumgartner.com/blog/wrapping-a-rust-crate-in-a-python-package/", "published_at": "2023-01-05T11:43:13+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0d84943f", "title": "Learning Rust With Advent of Code 2022", "url": "https://www.peterbaumgartner.com/blog/learning-rust-with-advent-of-code-2022/", "published_at": "2022-12-27T11:44:27+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0de0d3f9", "title": "Bootstrapped Sampling for Annotation: A Multiverse of Madness?", "url": "https://www.peterbaumgartner.com/blog/bootstrap-part-2-irr-multiverse/", "published_at": "2022-11-10T08:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0edfc1c3", "title": "\"How much data do I need to label?\" - The Bootstrapped Inter-Rater Reliability Answer", "url": "https://www.peterbaumgartner.com/blog/how-much-data-bootstrap-irr/", "published_at": "2022-10-28T15:39:27+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce0f593ac4", "title": "Reasons to Blog: A Rebuttal to Myself", "url": "https://www.peterbaumgartner.com/blog/reasons-to-blog-a-rebuttal-to-myself/", "published_at": "2022-10-05T15:24:56+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce10356e40", "title": "What Should Data Scientists Learn?", "url": "https://www.peterbaumgartner.com/blog/what-should-data-scientists-learn/", "published_at": "2022-04-20T17:59:50+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce10e8fe3b", "title": "An Introduction to Just Enough Cython to be Useful", "url": "https://www.peterbaumgartner.com/blog/intro-to-just-enough-cython-to-be-useful/", "published_at": "2022-03-01T00:58:19+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce11d92118", "title": "Python Virtual Environment & Packaging Workflow", "url": "https://www.peterbaumgartner.com/blog/python-virtual-environment-package-workflow/", "published_at": "2022-01-29T01:19:35+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1219d5d0", "title": "My Personal History with NLP or Side-Effects of Good API Design", "url": "https://www.peterbaumgartner.com/blog/personal-history-and-api-design/", "published_at": "2022-01-16T12:39:47+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce12f0908d", "title": "Two Logging Options Better than Print Statements", "url": "https://www.peterbaumgartner.com/blog/logging-beyond-print/", "published_at": "2022-01-13T02:02:41+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce13c1fc25", "title": "Ways I Use Testing as a Data Scientist", "url": "https://www.peterbaumgartner.com/blog/testing-for-data-science/", "published_at": "2021-12-23T00:48:32+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce14aa8f5d", "title": "Notes on NLP for Survey Design", "url": "https://www.peterbaumgartner.com/blog/nlp-surveys/", "published_at": "2021-12-14T02:06:35+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1525d2a0", "title": "Incorporating Julia Into Python Programs", "url": "https://www.peterbaumgartner.com/blog/incorporating-julia-into-python-programs/", "published_at": "2021-08-09T15:35:27+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce15a498e0", "title": "The Fastest Way to Load Data Into Your Django Project using PostgreSQL", "url": "https://www.peterbaumgartner.com/blog/the-fastest-way-to-load-data-django-postgresql/", "published_at": "2019-10-08T09:52:23+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce168e42d2", "title": "Tableau and Raw Data as Sneaky Technical Debt", "url": "https://www.peterbaumgartner.com/blog/tableau-as-sneaky-technical-data-debt/", "published_at": "2019-07-30T17:27:47+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1754dccb", "title": "Making the Most of spaCy's Rule-Based Matcher", "url": "https://www.peterbaumgartner.com/blog/spacy-rule-based-matcher-workflow/", "published_at": "2019-07-18T00:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce17f98762", "title": "Dimension Reduction with UMAP and Plotly Scatterplot", "url": "https://www.peterbaumgartner.com/notebooks/umap-to-plotly/", "published_at": "2019-07-17T00:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce187c0af2", "title": "Applied NLP: Lessons from the Field", "url": "https://www.peterbaumgartner.com/blog/applied-nlp-lessons/", "published_at": "2019-07-06T06:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1959f358", "title": "Fine-Tuning GPT-2 Small for Generative Text", "url": "https://www.peterbaumgartner.com/blog/gpt2-jokes/", "published_at": "2019-03-23T15:16:39+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce19872755", "title": "Potential Issues with Criminal Justice Data", "url": "https://www.peterbaumgartner.com/blog/issues-with-criminal-justice-data/", "published_at": "2018-08-06T16:40:29+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1a2780fe", "title": "Notes on NLP Projects", "url": "https://www.peterbaumgartner.com/blog/notes-on-nlp-projects/", "published_at": "2018-08-06T14:59:48+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1ae579d6", "title": "Holy NLP! Understanding Part of Speech Tags, Dependency Parsing, and Named Entity Recognition", "url": "https://www.peterbaumgartner.com/notebooks/holy-nlp/", "published_at": "2018-05-19T00:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1b8afbdb", "title": "Holy NLP! Understanding Part of Speech Tags, Dependency Parsing, and Named Entity Recognition", "url": "https://www.peterbaumgartner.com/blog/holy-nlp/", "published_at": "2018-05-18T01:29:07+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1be7efc8", "title": "Word Embeddings Explainer", "url": "https://www.peterbaumgartner.com/blog/word-embeddings-explainer/", "published_at": "2018-04-30T19:22:07+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1c2a5740", "title": "How to Test IPython Magic", "url": "https://www.peterbaumgartner.com/blog/testing-ipython-magics/", "published_at": "2018-02-16T00:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1ca6ef87", "title": "An Exploration in Earth & Word Movers Distance", "url": "https://www.peterbaumgartner.com/blog/word-movers-distance-exploration/", "published_at": "2017-06-18T00:00:00+00:00" }, { "id": "01a087c0-12e3-73ec-b234-abce1cd2174f", "title": "An Exploration in Earth & Word Movers Distance", "url": "https://www.peterbaumgartner.com/notebooks/word-movers-distance-exploration/", "published_at": "2017-06-18T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb10277ac612", "title": "Spacy Rule Based Matcher Workflow", "url": "https://www.peterbaumgartner.com/notebooks/spacy-rule-based-matcher/", "published_at": "2017-05-21T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb1027991088", "title": "The Impact of Model Output Transformations on ROC", "url": "https://www.peterbaumgartner.com/blog/output-transformations-roc-impact/", "published_at": "2017-05-21T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb1028963115", "title": "The Impact of Model Output Transformations on ROC", "url": "https://www.peterbaumgartner.com/notebooks/output-transformations-roc-impact/", "published_at": "2017-05-21T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb10294de8b1", "title": "Colored ROC Curves", "url": "https://www.peterbaumgartner.com/notebooks/colored-roc-curves/", "published_at": "2017-04-04T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb102a29e819", "title": "Biclustering (with Paul Revere)", "url": "https://www.peterbaumgartner.com/notebooks/biclustering-with-paul-revere/", "published_at": "2017-03-29T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb102a6aa800", "title": "Dimension Reduction with TSNE and Bokeh Scatterplot", "url": "https://www.peterbaumgartner.com/notebooks/tsne-to-bokeh/", "published_at": "2017-03-25T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb102b0670dc", "title": "Some Tips for Using Jupyter Notebooks with Pelican", "url": "https://www.peterbaumgartner.com/blog/jupyter-notebooks-for-pelican/", "published_at": "2017-03-17T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb102b4e9cc0", "title": "PyData Carolinas Recap & Presentation Reflection", "url": "https://www.peterbaumgartner.com/blog/pydata-carolinas-recap/", "published_at": "2016-09-17T00:00:00+00:00" }, { "id": "01a087c0-12e4-7020-bd57-fb102c09a37a", "title": "Creating Slack Slash Commands with Python and Flask: Part 1", "url": "https://www.peterbaumgartner.com/blog/slack-commands-with-python-and-flask/", "published_at": "2016-01-18T00:00:00+00:00" } ] posts Claim your blog
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2026

Agent Token Costs Are System Costs: Evaluate Your Agentic Tooling End-to-Endoriginal ↗
13 Jun 2026

2024

Reporting With Quartooriginal ↗
5 Feb 2024

2023

Wrapping a Rust Crate in a Python Packageoriginal ↗
5 Jan 2023

2022

Learning Rust With Advent of Code 2022original ↗
27 Dec 2022
Bootstrapped Sampling for Annotation: A Multiverse of Madness?original ↗
10 Nov 2022
"How much data do I need to label?" - The Bootstrapped Inter-Rater Reliability Answeroriginal ↗
28 Oct 2022
Reasons to Blog: A Rebuttal to Myselforiginal ↗
5 Oct 2022
What Should Data Scientists Learn?original ↗
20 Apr 2022
An Introduction to Just Enough Cython to be Usefuloriginal ↗
1 Mar 2022
Python Virtual Environment & Packaging Workfloworiginal ↗
29 Jan 2022
My Personal History with NLP or Side-Effects of Good API Designoriginal ↗
16 Jan 2022
Two Logging Options Better than Print Statementsoriginal ↗
13 Jan 2022

2021

Ways I Use Testing as a Data Scientistoriginal ↗
23 Dec 2021
Notes on NLP for Survey Designoriginal ↗
14 Dec 2021
Incorporating Julia Into Python Programsoriginal ↗
9 Aug 2021

2019

The Fastest Way to Load Data Into Your Django Project using PostgreSQLoriginal ↗
8 Oct 2019
Tableau and Raw Data as Sneaky Technical Debtoriginal ↗
30 Jul 2019
Making the Most of spaCy's Rule-Based Matcheroriginal ↗
18 Jul 2019
Dimension Reduction with UMAP and Plotly Scatterplotoriginal ↗
17 Jul 2019
Applied NLP: Lessons from the Fieldoriginal ↗
6 Jul 2019
Fine-Tuning GPT-2 Small for Generative Textoriginal ↗
23 Mar 2019

2018

Potential Issues with Criminal Justice Dataoriginal ↗
6 Aug 2018
Notes on NLP Projectsoriginal ↗
6 Aug 2018
Holy NLP! Understanding Part of Speech Tags, Dependency Parsing, and Named Entity Recognitionoriginal ↗
19 May 2018
Holy NLP! Understanding Part of Speech Tags, Dependency Parsing, and Named Entity Recognitionoriginal ↗
18 May 2018
Word Embeddings Explaineroriginal ↗
30 Apr 2018
How to Test IPython Magicoriginal ↗
16 Feb 2018

2017

An Exploration in Earth & Word Movers Distanceoriginal ↗
18 Jun 2017
An Exploration in Earth & Word Movers Distanceoriginal ↗
18 Jun 2017
Spacy Rule Based Matcher Workfloworiginal ↗
21 May 2017
The Impact of Model Output Transformations on ROCoriginal ↗
21 May 2017
The Impact of Model Output Transformations on ROCoriginal ↗
21 May 2017
Colored ROC Curvesoriginal ↗
4 Apr 2017
Biclustering (with Paul Revere)original ↗
29 Mar 2017
Dimension Reduction with TSNE and Bokeh Scatterplotoriginal ↗
25 Mar 2017
Some Tips for Using Jupyter Notebooks with Pelicanoriginal ↗
17 Mar 2017

2016

PyData Carolinas Recap & Presentation Reflectionoriginal ↗
17 Sept 2016
Creating Slack Slash Commands with Python and Flask: Part 1original ↗
18 Jan 2016