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header(“11. DISORDERED STRUCTURE -> ORDERED APPROXIMATION”) disordered = Structure( Lattice.cubic(3.6), [{“Cu”: 0.5, “Au”: 0.5}], [[0, 0, 0]], ) disordered.make_supercell([2, 2, 2]) print(“Disordered composition:”, disordered.composition) try: disordered_oxi…

In this tutorial, we build an uncertainty-aware large language model system that not only generates answers but also estimates the confidence in those answers. We implement…

SWARM_TOOLS = [ { “type”: “function”, “function”: { “name”: “task_update”, “description”: “Update the status of a task. Use ‘in_progress’ when starting, ‘completed’ when done.”, “parameters”: {…

import os, sys, subprocess, importlib, pathlib SENTINEL = “/tmp/diffrax_colab_ready_v3” def _run(cmd): subprocess.check_call(cmd) def _need_install(): try: import numpy import jax import diffrax import equinox import optax import…

Image by Author   # Introduction  When you solve enough interview-style data problems, you start noticing a funny effect: the dataset “shape” quietly dictates your coding style.…

In this tutorial, we build an enterprise-grade AI governance system using OpenClaw and Python. We start by setting up the OpenClaw runtime and launching the OpenClaw…

In the fast-moving world of agentic workflows, the most powerful AI model is still only as good as its documentation. Today, Andrew Ng and his team…

In this tutorial, we build a complete pipeline for single-cell RNA sequencing analysis using Scanpy. We start by installing the required libraries and loading the PBMC…

In this tutorial, we implement a production-grade, large-scale graph analytics pipeline in NetworKit, focusing on speed, memory efficiency, and version-safe APIs in NetworKit 11.2.1. We generate…

In this tutorial, we explore how we use Daft as a high-performance, Python-native data engine to build an end-to-end analytical pipeline. We start by loading a…