📓 Jupyter Notebooks - 2601

Less-relevant results

Fast Exact Nearest-Neighbor Learning for High-Frequency Financial Time Series

🤖AI Academic

arxiv.org·

Elements of Cryptanalysis: From Al-Kindi to Post-Quantum Standards — Elements of Cryptanalysis: From Al-Kindi to Post-Quantum Standards

📡Information Theory

bnaskrecki.faculty.wmi.amu.edu.pl·

Ask HN: Pandas to Polars migration, from 200s timeouts to under 4s. Anyone else?

📋JSON Parsing Discussion

news.ycombinator.com··Hacker News

kelu124/Resume_RDF_update: Parse a CV into a structured Turtle RDF knowledge graph using the ResumeRDF ontology via a password-protected Streamlit web app or a standalone Python script.

🕸️Knowledge Graphs Code

github.com··Hacker News

From Jupyter Notebook to production: How to ship AI systems that actually work

📚Self-Documenting Code

thenewstack.io··Hacker News

Optimal Seating on the Airbus A380

🦆DuckDB Blog

tech.marksblogg.com··Hacker News

TIL: Setting a custom price for a model in AgentsView

✨Gleam

simonwillison.net·

Show HN: Typedframes – Pandas/polars column name checking at lint time

📐Type Theory Code

github.com··Hacker News

fastai: style

🤖AI Reference

docs.fast.ai··Hacker News

Tejas-TA/predikit: The missing bridge between your ML models and your AI agents.

🤖AI Code

github.com··Hacker News

What is Agentic RAG? Building Multi-Agent Agentic RAG Systems

🔍RAG

pub.towardsai.net

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

🤖AI Code

github.com··Hacker News

Understanding Principal Component Analysis (PCA)

📡Signal Processing Blog

medium.com·

rentruewang/inversql: Create SQL that match your selection (with explainable AI), not the other way around

💡Explainable AI Code

github.com··Hacker News

I Can Compress 1000 Dimensions Into 2 — Here’s What PCA Taught Me

📡Signal Processing

pub.towardsai.net

Issue 654

🔄Systems Thinking Blog

datascienceweekly.substack.com··Substack

The Read Model Zoo: Projections Beyond Tables - EventSourcingDB

🕸️Graph Databases Blog Reference

docs.eventsourcingdb.io··Hacker News

Can You Trace any Prediction Back to the Exact Data that Caused it? Here’s How I Built that

🗺️Region Inference

pub.towardsai.net

Show HN: SuperTree – interactive decision tree plot for sklearn,xgboost,lightgbm

Building a Production-Inspired CSV to PostgreSQL ETL Pipeline with Python

Fast Exact Nearest-Neighbor Learning for High-Frequency Financial Time Series

Elements of Cryptanalysis: From Al-Kindi to Post-Quantum Standards — Elements of Cryptanalysis: From Al-Kindi to Post-Quantum Standards

Ask HN: Pandas to Polars migration, from 200s timeouts to under 4s. Anyone else?

kelu124/Resume_RDF_update: Parse a CV into a structured Turtle RDF knowledge graph using the ResumeRDF ontology via a password-protected Streamlit web app or a standalone Python script.

From Jupyter Notebook to production: How to ship AI systems that actually work

Optimal Seating on the Airbus A380

TIL: Setting a custom price for a model in AgentsView

Show HN: Typedframes – Pandas/polars column name checking at lint time

fastai: style

Tejas-TA/predikit: The missing bridge between your ML models and your AI agents.

What is Agentic RAG? Building Multi-Agent Agentic RAG Systems

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

Understanding Principal Component Analysis (PCA)

rentruewang/inversql: Create SQL that match your selection (with explainable AI), not the other way around

I Can Compress 1000 Dimensions Into 2 — Here’s What PCA Taught Me

Issue 654

The Read Model Zoo: Projections Beyond Tables - EventSourcingDB

Can You Trace any Prediction Back to the Exact Data that Caused it? Here’s How I Built that