Few-Shot Text Classification with Scikit-LLM
Leveraging Scikit-LLM for one of the simplest yet most practical text classification tasks utilized in the modern AI landscape: few-shot classification.
KDnuggets6 min read
scikit-learn
32 stories
Voting on Features: Federated Feature Selection Without Sharing Data
Hospitals, banks, and edge devices can agree on which features matter by sharing votes instead of rows, runnable in NVIDIA FLARE and Flower The post Voting on Features: Federated Feature Selection Without Sharing Data appeared first on Towards Data Science.
Towards Data Science20 min readBuilding 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 retrieval and open-source models for embeddings and...
Machine Learning Mastery Blog7 min read15 Flask Projects With Source Code (Beginner to Advanced)
Most people learn Flask by reading documentation, then get stuck at “what do I build now?” A Flask project is the fastest way to close that gap, you write real routes, connect a real database, and ship something you can link to on your resume.
AI and Machine Learning Roadmaps Blog9 min readMaking Intent Routing Explainable
Making Intent Routing Explainable: Calibrated Probabilities, Decision Records and a Four-Tier Cascade
Towards AI34 min readWhen not Modeling is the Pragmatic Decision
When not Modeling is the Pragmatic Decision An anonymized forecasting case reconstructed with synthetic data: regime shifts, pretrained models and production judgment A few months ago I was involved …
Towards AI10 min readOpus 5.5 is good at explainer videos
Checking in on Opus 5.5 ~1 week after launch. It's the #1 model in share of spend and share of tokens among Anthropic models on OpenRouter Switching from Opus 5 has been particularly rapid
Latent Space21 min readHow to Catch Data Drift When Every Feature Looks Normal
Detect hidden shifts in feature relationships with adversarial validation and scikit-learn The post How to Catch Data Drift When Every Feature Looks Normal appeared first on Towards Data Science.
Towards Data Science13 min readThe Future of Latent Space
A quiet day lets us discuss the work behind the scenes - now open for business!
Latent Space20 min readCommunity Voices: Interview with Lucy Liu, scikit-learn core maintainer
scikit-learn is one of the most widely used tools in data science, counting over 200 million downloads every month. You may know it as the Python library, but behind the code there is a global community that develops, maintains, and sustains it for the benefit of all data scientists all over the…
Scikit-Learn Documentation Blog6 min read🔬 An Oscar, Two Asteroids, and the Algorithm in Your sklearn: John Platt on AI for Science
We talked to Google’s Oscar winning “Giganerd” about automating science, solving climate change, and how future generations can contribute to science in the age of superintelligent AI
Latent Space8 min readMonitoring Embedding Drift in Production Scikit-LLM Pipelines
In this article, you will learn what embedding drift is, why it matters for production large language models, and how to implement two practical techniques...
Machine Learning Mastery7 min readMultilingual Text Classification with Scikit-LLM and Multilingual Embeddings
In this article, you will learn how to build a multilingual text classification pipeline using multilingual large language model (LLM) embeddings and Scikit-learn, without training...
Machine Learning Mastery6 min readMachine learning model deployment
Machine learning model deployment moves trained models to production. Learn deployment patterns for ML models, CI/CD, and feature-flag rollouts.
Launch Darkly22 min readLightpanda for Python: a browser in one pip install
pip install lightpanda gives you a headless browser and its Python bindings in one command, browser included. Scrape JavaScript-rendered pages and hand the data straight to pandas.
Lightpanda Blog8 min readWhat a Machine Learning Model is and How to Make One
Machine learning can sound much more complicated than it actually is. You hear words like models, training, features, datasets, predictions, and algorithms, and it can feel like you need a PhD in math
freeCodeCamp — Artificial Intelligence25 min readAn Update on Metadata Routing
Author: Stefanie Senger This blog post is a cross-post of a Probabl blog post and based on a talk given at EuroSciPy 2026 in Kraków (slides).
Scikit-Learn Documentation Blog7 min readscikit-learn release 1.9: better numerics, new core functionality
Scikit-learn 1.9 release is out, and it comes with solid improvements to many existing estimators, making them faster, more stable, handling missing values, adding GPU support… The release also enhances the estimator displays in notebooks, and introduces a callback mechanism that opens the door to…
Scikit-Learn Documentation Blog3 min read
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