iiinova — where your digital self keeps evolving

Alex Tantos @alextantos.bsky.social · 12/11/2025

2/2 Markdown rendering everywhere: lessons, questions, hints and menus are now displayed with MD formatting, making everything easier to read in the REPL. The built-in Julia Basics course has been adapted to use these new features. Check it out in action here: youtu.be/aEboVhipEfg #JuliaLang

youtu.be

Swirl.jl: Multi-step code questions and full Markdown rendering!

YouTube video by Alex Tantos

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Alex Tantos @alextantos.bsky.social · 12/11/2025

Swirl.jl now supports multi-step code questions and full Markdown rendering! 🌀 1/2 Multi-step questions: you can now design exercises that require multiple code lines, with separate hints for each step. Perfect for walking learners through multi-part problems or short coding tasks.

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Alex Tantos @alextantos.bsky.social · 10/11/2025

🌀 Swirl.jl is here! An interactive learning platform that teaches JuliaLang in the REPL. ✨ Features 🎓 Interactive code checks 📚 Structured lessons 💾 Auto-save 🎮 Reset anytime For now, Julia Basics is the only course. It will be expanded and new courses are on the way. github.com/atantos/Swir...

github.com

GitHub - atantos/Swirl.jl: Swirl.jl is an interactive learning platform for Julia that runs entirely in the console/terminal, inspired by the popular swirl package for R. It provides a hands-on, guide...

Swirl.jl is an interactive learning platform for Julia that runs entirely in the console/terminal, inspired by the popular swirl package for R. It provides a hands-on, guided learning experience wh...

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Alex Tantos @alextantos.bsky.social · 29/10/2025

comparison.parameters → tunable parameters used for the building of the "comparison" object.

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Alex Tantos @alextantos.bsky.social · 29/10/2025

comparison.effect_sizes → pairwise differences & Cohen’s d

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Alex Tantos @alextantos.bsky.social · 29/10/2025

comparison.summary → number of collocates & mean scores

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Alex Tantos @alextantos.bsky.social · 29/10/2025

comparison.results → collocates & scores per year (see the table below for the year 1814)

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Alex Tantos @alextantos.bsky.social · 29/10/2025

What this call does 1️⃣ Splits the corpus into subcorpora by :year. 2️⃣ Analyzes each subcorpus using LLR to compute collocates of node_word. 3️⃣ Aggregates everything into structured outputs👇 #JuliaLang #CorpusLinguistics #AssociationAnalysis #TextAssociations.jl #NLP #DigitalHumanities

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Alex Tantos @alextantos.bsky.social · 29/10/2025

julia>comparison = compare_subcorpora( corpus_df, :year, # Split corpus by year node_word, # Word to analyze LLR; # Association (Log-Likelihood Ratio) windowsize = 5, minfreq = 1 ) #JuliaLang #CorpusLinguistics #AssociationAnalysis #TextAssociations.jl #NLP #DigitalHumanities

atantos.github.io

Home · TextAssociations.jl

Documentation for TextAssociations.jl.

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Alex Tantos @alextantos.bsky.social · 29/10/2025

If you’re exploring linguistic change across Austen’s novels (1811–1817), you might want to ask questions like: 👉 Did the verb “might” become more associated with epistemic verbs after 1814? 👉 Which collocates changed most between 1811 and 1817? This single line in JuliaLang does all the lifting 👇

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Alex Tantos @alextantos.bsky.social · 26/10/2025

Here is the mental model for TextAssociations.jl users: Raw Text / Corpus ↓ ContingencyTable ↓ CorpusContingencyTable ↓ assoc_score(::Type{<:AssociationMetric}, x::AssociationDataFormat; kwargs...) ↓ Metric evaluator (eval_pmi, …) ↓ Result as DataFrame (or Vector if scores_only=true)

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Alex Tantos @alextantos.bsky.social · 26/10/2025

Here’s a 37-second sneak peek showing how the TextAssociations.jl package computes a Bayesian-smoothed version of PMI for the word "might" across Jane Austen’s novels, from text normalization and corpus loading to contingency-table construction and metric calculation. #JuliaLang #CorpusLinguistics

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Alex Tantos @alextantos.bsky.social · 13/10/2025

And here is the resulting DataFrame #JuliaLang #TextAssociations.jl

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Alex Tantos @alextantos.bsky.social · 12/10/2025

In the attached snapshot, contingency tables are generated capturing words occurring within a 5-word window around "innovation" and PMI scores quantify their association strength. The top 5 collocates are then displayed in a DataFrame. #TextAssociations #JuliaLang

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Reposted by Alex Tantos

Simon Danisch @simi.bsky.social · 07/10/2025

Finally announcing Bonito.jl! 🎉 A Julia web framework that went from "neglected prototype" to something I'm genuinely proud of. Reactive UIs, rich widgets, Makie integration, deploy anywhere (Jupyter/VSCode/web/static HTML) makie.org/website/blog...

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Alex Tantos @alextantos.bsky.social · 04/10/2025

The package is now publicly available as an early release (not yet registered in the Julia package registry), and you can already explore its functionality on GitHub: 🔗 github.com/atantos/Text... Feedback, ideas, and experiments are welcome. 7/7

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

Many well-known and lesser-known association measures, together with tools for collocation network analysis, are now coming together under one roof complemented by powerful corpus-based functionality. 6/n

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

revealing what is salient within a given dataset, discourse, or community. A new #JuliaLang package, TextAssociations.jl, is taking shape, laying the groundwork for exploring how words connect and co-occur in a transparent, data-driven way. 5/n

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

under one roof, alongside corpus-based functionality. While embeddings and RAG systems operate within pretrained semantic spaces, association measures remain essential for interpretable, corpus-based insights. They quantify how often words co-occur beyond what chance would predict, 1/4

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

A new Julia package called TextAssociations is taking shape, building a foundation for studying how words connect and co-occur in a transparent, data-driven way. Many familiar and less familiar association measures as well as the building collocation network analysis are finally coming together 3/n

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

While embeddings and RAG systems operate on pretrained semantic spaces, association measures remain essential for interpretable, corpus-based evidence. They quantify how often words co-occur compared to chance, showing what is salient within a specific dataset or community. 2/n

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 04/10/2025

In language-related and digital humanities research, we are often concerned not only with meaning, but also with pattern and context — how words cluster within a discourse or register, across time periods, or within particular language varieties such as dialects and learner corpora. 1/n

github.com

GitHub - atantos/TextAssociations.jl

Contribute to atantos/TextAssociations.jl development by creating an account on GitHub.

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Alex Tantos @alextantos.bsky.social · 05/12/2024

Thank you for your kind words!

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Alex Tantos @alextantos.bsky.social · 30/11/2024

I’ve created a GitHub repo where I’m translating the #Python code from @rasbt's Build a LLM from Scratch into #JuliaLang. I’d love for Julia enthusiasts to explore it and I’d be eager to see contributions and improvements. Don’t hesitate to ⭐ it! #LLMs #AI github.com/atantos/Buil...

github.com

GitHub - atantos/Build_LLMs_from_Scratch_in_Julia

Contribute to atantos/Build_LLMs_from_Scratch_in_Julia development by creating an account on GitHub.

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Reposted by Alex Tantos

Julia Language @julialang.org · 30/11/2024

If you haven't found it already be sure to subscribe to the #JuliaDispatch podcast by @chrisrackauckas.bsky.social and Michael Tiemann! This week's special guest is Παναγιώτης Γεωργακόπουλος to discuss the #PlutoJL project. youtu.be/TknY3rE1TeE?...

youtu.be

Pluto.jl with Panagiotis Georgakopoulos

YouTube video by Julia Dispatch

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Alex Tantos @alextantos.bsky.social · 28/11/2024

Here is the Medium link: atantos.medium.com/computing-at... And if you are not a Medium member, here is the friend link: atantos.medium.com/computing-at... #LLMs #Python #JuliaLang #Transformers #Attention #GenAI 2/2

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Alex Tantos @alextantos.bsky.social · 28/11/2024

Continuing my journey of translating @rasbt 's "Build a LLM (from Scratch)" Python code to Julia, my latest Medium article focuses on computing attention weights for all input tokens as discussed in section 3.3.2. #LLMs #Python #JuliaLang #Transformers #Attention #GenAI 1/2

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Alex Tantos @alextantos.bsky.social · 23/11/2024

Thanks a lot for sharing my medium article with the Julia discourse — I really appreciate it! 😊 I'm glad to hear there's interest, and I'll take a look at the thread and respond later today!

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Alex Tantos @alextantos.bsky.social · 21/11/2024

Here is the Medium link: atantos.medium.com/implementing... And if you are not a Medium member, here is the friend link: atantos.medium.com/implementing... #LLMs #Python #JuliaLang #Transformers #attention #AI 2/2

atantos.medium.com

Implementing a Simple Self-Attention Mechanism with Python and Julia

No medium membership? Read this article for free here.

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Alex Tantos @alextantos.bsky.social · 21/11/2024

Inspired by @rasbt Build a LLM (from Scratch), I’ve written a Medium article on implementing a simple self-attention mechanism using Python and Julia. It includes practical, theory-driven details to deepen understanding. #LLMs #Python #JuliaLang #Transformers #Attention #AI 1/2

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Alex Tantos @alextantos.bsky.social · 19/11/2024

Ok! Here we are! Blue clean skies ahead..

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Alex Tantos @alextantos.bsky.social · 14/01/2024

Just another day spent living life instead of posting about it...

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Alex Tantos @alextantos.bsky.social · 12/01/2024

How I missed these original twitter colors! #throwback

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