The 150-sample Iris dataset used by the K-means article.

Includes standardization, K-means++ initialization, restarts, and SSE selection.

SVG flowchart for the C program execution path.

A 2D scatter projection using petal length and petal width.

Contains dataset, source code, flowchart, and visualization.

The article includes a runnable scikit-learn classification script.

The C source for the handwritten digit softmax classifier.

Compressed handwritten digit training set with 42000 labeled samples.

Compressed handwritten digit test set with 28000 unlabeled samples.

The official submission format example for checking the final output columns.

The prediction file generated by the current C project.

The compact softmax demo model and sample set used by the browser playground.

A small handwritten digit preview grid extracted from the training set.

Contains the source file, compressed datasets, submission files, browser model, and preview grid.

Single-file C tiny CNN with CIFAR-10 loading, convolution, pooling, softmax, and backpropagation.

Model weights generated by one local small-sample run.

Sample test prediction output from the CIFAR-10 tiny CNN.

Companion explanation material for the CNN project.

A redacted mld_chaffing_v2.py control-flow skeleton with secrets, node topology, and target lists removed.

A redacted CSV template for CPU, memory, peak threads, pulse rate, latency, and error measurements.

A CSV template for TP, FN, FP, TN, accuracy, precision, recall, F1, ROC-AUC, entropy, and JS divergence.

Notes explaining why the public resources include only redacted code, test templates, and architecture context.

Setup, safety boundaries, and quick-run commands for the AI Security series.

Includes safe toy scripts, result CSVs, risk register, attack-defense matrix, and architecture diagram.

CSV risk register template for AI threat modeling and release review.

Maps attack surface, toy demo, metric, and defensive control into one CSV table.

Shows threat modeling, robustness, data integrity, model privacy, and RAG guardrails.

FGSM-style perturbation and accuracy-drop experiment for a local digits classifier.

Demonstrates poison rate, trigger behavior, and attack success rate on digits.

Outputs membership AUC, target accuracy, surrogate fidelity, and surrogate accuracy.

Uses a deterministic toy agent to demonstrate external-data demotion and tool-policy blocking.

A 1200x630 SVG card for sharing the Deep Learning / CNN topic hub.

A 1200x630 SVG card for the K-means, Iris, and ML workflow topic hub.

A 1200x630 SVG card for eight queens, backtracking, bitmasks, and the playground.

A 1200x630 SVG card for handwritten digits, C classifiers, and browser demos.

Four 45-60 second storyboard scripts ready for later Remotion production.

An 8-second Remotion animation showing how a 3x3 convolution kernel scans an input and builds a feature map.

A Remotion clip showing sample assignment, centroid updates, and SSE reduction.

A Remotion clip showing row-by-row search, conflict pruning, and backtracking.