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Towards Data Science
Oct 16, 2026
Deploying Data Science Tools: Part 1
Getting your data science code running anywhere
The post Deploying Data Science Tools: Part 1 appeared first on Towards …
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Towards Data Science
Oct 17, 2026
When EEG Models See the Same People in Training and Testing
How participant-aware evaluation changed performance across three machine-learning models
The post When EEG Models See t…
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Towards Data Science
Oct 15, 2026
Jev Your Engines: Seven Open Decision Models vs. a Generative LLM
A hands-on Jev repo comparison of routing accuracy, latency, and output reliability
The post Jev Your Engines: Seven Ope…
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ML Mastery
Oct 13, 2026
Building a RAG Pipeline with LLM Embeddings and Scikit-learn
In this article, you will learn how to build a lightweight, end-to-end RAG pipeline using scikit-learn for vector retrie…
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KDnuggets
Oct 20, 2026
The Roadmap to Becoming an AI Product Manager in 2026
A structured four-phase roadmap for building the technical fluency, evaluation skills, and governance literacy needed to…
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ML Mastery
Oct 14, 2026
Building a Custom LLM Evaluation Harness in Python from Scratch
In this article, you will learn how to build a custom LLM evaluation harness in Python from scratch, structured around f…
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Towards Data Science
Oct 15, 2026
What OpenAI’s 719 Math Papers Mean for Data Science
Matching messy text, choosing representative examples, and generating comparison data.
The post What OpenAI’s 719 Math P…
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Towards Data Science
Oct 20, 2026
What's in the Box? Distinguishing Acceptable Traces from Unacceptable Ones
Turn scattered requirements into deployable agents
The post What's in the Box? Distinguishing Acceptable Traces from Una…
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