An Introduction toΒ Jev
The AI that makes decisions instead of generating text
The post An Introduction toΒ Jev appeared first on Towards Data Science.
The AI that makes decisions instead of generating text
The post An Introduction toΒ Jev appeared first on Towards Data Science.
Weather-sensitive industries increasingly have access to observations that offer an earlier, more local view of changing conditions. Energy companies collect measurements across wind and solar assets, emergency management teams rely on radar and local sensors, and satellite providers continuously observe the Earth. This data helps organizations understand and manage physical risk across sectorsβ¦
How to put a dollar value on your organization's operational data
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How do you set yourself up for a career that will stand the test of time when things are changing so fast?
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From a chocolate bar with no price tag to a marketing mix model in PyMC, and the 200-year-old integral that stood in between.
The post Why You Think Like a Bayesian but Were Taught Like a Frequentist appeared first on Towards Data Science.
Robust Estimation Series: comparing classical and modern robust estimators through theory, code, and experiments
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Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the challenge shifts from running an algorithm to operating shared infrastructure. GPUs must be allocated when jobs need them, multiple research studies must remain separated, and every participating organization must retain control of its ownβ¦
How statistical moments connect the mean, the variance, and higher powers of a distribution
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Before reaching for an LLM API on every classification problem, it's worth knowing what a decades-old baseline can already do with the labeled data you have β and exactly how much more data buys you.
The post How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It. appeared first on Towards Data Science.
Frequentist confidence intervals and Bayesian credible intervals answer different questions, and confusing them can distort product decisions
The post The 95% Illusion: Why Your Confidence Interval Isn't What You Think It Is appeared first on Towards Data Science.
Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA BioNeMo Inference Runtime (BioIR) helps accelerate supported biomolecular structure-prediction models on NVIDIA GPUs while keeping the familiar PyTorch workflow. It uses optimized kernels and, where applicable, CUDA Graphs to speed modelβ¦
A model is only as reliable as the assumptions behind it
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Statistical thinking beyond formulas
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In September 2026, NVIDIA announced it is leaning into native GPU programming in Rust. CUDA C++ and CUDA Python are mature, enterprise-grade toolchains, and NVIDIA will be growing and maturing CUDA Rust into 2027 and beyond The systems layer of AI spans inference engines, serving infrastructure, drivers, and agent runtimes, and it churns constantly as models and techniques change.
AI companies quietly watermark billions of words a day. Hereβs how to apply the same three families of techniques to your own writingβand what real experiments reveal about which watermarks survive copy-paste, editing, and paraphrasing.
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Using LDA for dimensionality reduction in classification problems
The post Linear Discriminant Analysis (LDA) in Real-Life: Dimensionality Reduction in a Real-Estate Dataset appeared first on Towards Data Science.
Why the default 50/50 split is the wrong move when your treatment is more expensive than your control, and how cost-based sampling weights fix it
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Power BI Premium is gone. Microsoft Fabric took its place. Here's what actually changed for you, what didn't, and where to start β without the panic.
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Why the standard groupBy function isnβtΒ enough
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What each one solves, and runnable code you can paste into a notebook.
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