A defensive walkthrough of the mld_chaffing_v2.py Virtual Mirror project: metadata leaks, entropy, distribution distance, confusion matrices, idle-window micro-pulses, and performance trade-offs.
Build and train a tiny CNN for CIFAR-10 image classification in C, with architecture, runnable commands, loss, accuracy, common errors, and improvement ideas.
A dataset-first walkthrough of the handwritten digit project, covering train.csv, test.csv, labels, and the 784-feature image representation.
A practical walkthrough of the C softmax classifier for handwritten digits, including logits, softmax probabilities, gradient updates, and CSV submission export.
Notes on the browser-side handwritten digit module, including the compact softmax demo model, sample browsing, drawing input, and probability inspection.
An accessible introduction to neurons, weights, bias, activation functions, forward propagation, backpropagation, and training loops.
A small end-to-end classification project using a built-in scikit-learn practice dataset, covering data loading, splitting, scaling, training, evaluation, and experiment notes.
An engineering-oriented walkthrough of the machine learning workflow, from problem definition and features to prediction and evaluation.
A beginner-friendly explanation of model parameters, loss functions, gradient descent, overfitting, and classification metrics.
A practical roadmap for programmers learning AI foundations, including the relationship between AI, machine learning, and deep learning.
