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How to Leverage NLP for Product Data Science
A practical guide to strengthening churn, CLV, and other traditional models with text
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Towards Data Science 人工智能
Synthetic-to-Real Transfer with Frozen DINOv3 Features
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Skill or MCP Server? Ask What Stops the LLM From Disobeying
Towards Data Science 人工智能
The Hidden Cost of LLM Routing: Why Switching Models Costs More
Towards Data Science 人工智能
What's in the Box? Distinguishing Acceptable Traces from Unacceptable Ones
Towards Data Science 人工智能
Welcome to Google Gemini 4 Argon
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Can Conformal Prediction Take You from Accurate to Reliable Machine Learning?
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How Many EEG Channels Do You Actually Need?
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AI Harms and Their Technical Causes
Towards Data Science 人工智能
Inferring the Host: A Bayesian Look at the Monty Hall Problem
"Always switch" is true for one particular host. Watch a few episodes and you can work out which host you've got. The post Inferring the Host: A Bayesian Look at the Monty Hall Problem appeared first on Towards Data…
Towards Data Science 人工智能
Both Charts Are Right. So Why Do They Disagree?
The statistical paradox that shows how combining data can reverse the story. The post Both Charts Are Right. So Why Do They Disagree? appeared first on Towards Data Science.
Towards Data Science 人工智能
The Number Your Quantization Gate Doesn't Have
Ten quantization guides, and not one threshold-dependent metric between them — what that gap hides, and the two numbers that close it. The post The Number Your Quantization Gate Doesn't Have appeared first on Towards…
Towards Data Science 人工智能
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 the Same People in Training and Testing appeared first on Towards Data Science.
Towards Data Science 人工智能
Do You Still Own the Code Your AI Wrote? I Built CodeOwnership to Measure It
I rated my confidence 4 out of 5, then couldn’t find a planted bug in 8 minutes. Here is the tool, the run, and its limits. The post Do You Still Own the Code Your AI Wrote? I Built CodeOwnership to Measure It appeared…
Towards Data Science 人工智能
I Built a Claim-Checker for Writing With Codex. It Passed a Wrong Claim.
The tool found the right passage but missed the mismatch, and the audit shows where rule-based checks break down. The post I Built a Claim-Checker for Writing With Codex. It Passed a Wrong Claim. appeared first on…
Towards Data Science 人工智能
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 Data Science.
Towards Data Science 人工智能
I Reran My Python 3.14 JIT Benchmarks on Python 3.15
The same three workloads show a much stronger JIT, but it still doesn't help every program The post I Reran My Python 3.14 JIT Benchmarks on Python 3.15 appeared first on Towards Data Science.
Towards Data Science 人工智能
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 Open Decision Models vs. a Generative LLM appeared first on Towards Data Science.
Towards Data Science 人工智能
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 Papers Mean for Data Science appeared first on Towards Data Science.
Towards Data Science 人工智能
How Many Guesses Does It Take to Crack an AI's "Random" Number?
I read the exact answer distribution from the logits of open models, base and instruction-tuned, and turned it into bits and guesses-to-crack. The post How Many Guesses Does It Take to Crack an AI's "Random" Number?…
Towards Data Science 人工智能
I Tested Four Ways to Give an AI Assistant a Memory. The Obvious One Was the Worst Value.
Pasting in the whole chat history cost 20 to 31 times more than looking up notes, and it did no better on the tasks. The post I Tested Four Ways to Give an AI Assistant a Memory. The Obvious One Was the Worst Value…
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