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Sarah Schürch's Q-learning agent starts knowing nothing and learns Tic Tac Toe over 10,000 games against a random opponent.
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We're thrilled to present Sam Everest's debut TDS article: a thorough, patiently explained guide to KANs (Kolmogorov–Arnold Networks). towardsdatascience.com/build…
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"BM25 did not survive because the field failed to invent something newer. It survived because dense retrieval solved a different problem."
Spyros Georgopoulos follows that tradeoff through the history of search, from exact keyword matching to dense vector retrieval and hybrid search. towardsdatascience.com/your-…
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"I believe the useful question is not how many cells there are, but how the tissue is compartmentalised, and what the distribution of one cell type tells us about another."
Daniel Manrique Castano picks up his series at the intersection of spatial analysis and neuroscience. towardsdatascience.com/where…
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Is the OpenAI Decisions API a JEV killer? Thomas Reid puts it through hands on tests and shares his verdict.
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Building LLM agents for production? This practitioner's guide from Partha Sarkar walks through six advanced architectural patterns worth knowing.
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Lambert Leong put seven open source Jev style decision models head to head with a generative LLM baseline. Find out which ones came out ahead and which ones fell behind.
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Customer sentiment often shifts before behavior does. Alex Davis shares a practical guide, with code, for bringing NLP into everyday product data science work.
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Borrowing from political science, Gadi Singer outlines a separation-of-powers framework for controlling complex agentic systems. towardsdatascience.com/who-w…
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"My hope is simple: to help people continue to challenge their cognition, become better decision-makers, create original insights, and remain relevant in an AI-powered world."
@rpdesai24 encourages all of us to get smarter — and explains how to go about it in concrete, actionable steps.
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"Add it up and you get more code than ever, less understanding of it, and a lot of the time we 'saved' quietly going into cleanup."
Gursimar Singh invites us to consider the tradeoffs we tacitly accept when we let AI tools take over the brunt of coding work. towardsdatascience.com/devel…
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"Each submission bundled several changes, and the live websites could vary, so the score alone does not show which fix mattered most. That is the gap I tried to look at on a small scale."
@DattijoMuhammad explores a worrisome browser-agent failure. towardsdatascience.com/i-bro…
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What can a decade old patent teach today's agent builders? Mario Noioso revisits his own work to show what it got right about loops and memory, and what it missed entirely.
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In his latest MLOps-focused guide, @Himansh70809561 explains what an iD column, a data string, and a missing value taught him about the blind spots of cross-validation. towardsdatascience.com/my-ma…
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Which AI coding assistant is more token-efficient, Claude Code or Cursor? Pratik Rupareliya goes beyond standard benchmarks to test real-world use cases. towardsdatascience.com/claud…
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One benchmark: Claude Code used 33K tokens, while Cursor used 188K.
Another: the exact reverse.
Token cost is a property of the task, not the tool. The field test that actually settles it: towardsdatascience.com/claud…
@TDataScience
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Irfan Alghani Khalid's Food Police reads a photo of his meal with the model built into macOS, Apple's Foundation Model, and logs every alert to a Google Sheet.
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For his latest exploration of agentic AI workflows, @BenjaminNweke11 zooms in on what happens when a tool breaks — but the dashboard stays green. towardsdatascience.com/agent…
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"The models reason fine, but [...] the underlying enterprise data isn't accessible, clean, or structured enough for them to act on reliably."
Partha Sarkar walks us through six advanced architectural patterns for data practitioners. towardsdatascience.com/data-…
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Not sure how to add guardrails to your LLM agents, or even whether you should? Shuai Guo unpacks the benefits, and outlines potential approaches to making your agentic systems more resilient. towardsdatascience.com/how-t…
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