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Data Science Espresso by Sarah Lea

Machine Learning, Deep Learning and Data Science simplified and served to your coffee break☕!

Newsletter · By Data Science Espresso by Sarah · English · Official site

Indexed issues, last 90 days
3
Latest publication
Sep 19, 2026
Audience
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Earliest in this view
Jul 13, 2026

Latest issues

  1. Issue · Sep 19, 2026

    From Word to Obsidian and Claude Code: How I Write Academic Papers Now (opens the original)

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    I opened an empty folder in VS Code, started Claude Code and entered /obsitex:obsitex-init. After eleven questions, the folder contained a complete project for a seminar paper: section files with placeholders, a bibliography and a file with all the settings for the conversion. In the Obsitex web app, I selected the folder and then opened the PDF:<a class="image-link image2 is-viewable-img" href="https://substackcdn.com/image/fetch/$s_!0LNL!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fs

  2. Issue · Aug 19, 2026

    RAG or a 1M Token Context Window? (opens the original)

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    When Kimi K3 came out in July with a context window of one million tokens, I asked myself the question a lot of people probably did: can I skip RAG now?A selection of what I have published over the last two years adds up to 127,068 tokens. This is twelve percent of the window. With that in mind, I ran a small experiment: I asked the same twelve questions, but once through a RAG pipeline with the top five chunks and once with all 32 articles in the prompt. The rest remained the same: I used the s

  3. Issue · Jul 13, 2026

    Building a Multi-Agent Support Ticket Triage With LangGraph (opens the original)

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    Imagine it is Monday morning and 80 new support tickets are sitting in the inbox.Most of them are routine:a password reseta “how do I change my email” questiona billing question that comes up ten times a weekAnd somewhere in that pile sits the one ticket that actually matters:“I was charged twice and I need a refund today.”During my time as an IT consultant at an SME, this was one of the most tedious problems I constantly faced.This week, I rebuilt that exact workflow as a small team of AI agent

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