Categorized blog
Read by project
Posts are grouped into AI, algorithm implementation, and site-building projects, with level, reading time, and stack metadata.
Series
Deep Learning Math Visualized
Five posts move from matrix calculus, backpropagation, optimizers, convolution, and attention, each with hand calculation, code, figures, and animation.
5 postsMatrix Calculus for Neural Networks
Derive dL/dW for y = Wx + b and verify it with finite differences.
Backpropagation as a Computation Graph
Trace local gradients through ReLU and softmax cross-entropy in a two-layer MLP.
Gradient Descent and Optimizer Geometry
Compare gradient descent, momentum, and Adam on a visible quadratic loss surface.
Convolution and Receptive Field Math
Compute convolution output size, receptive fields, channel mixing, and im2col layout.
Transformer Attention Math
Hand-calculate Q/K/V scores, softmax weights, masks, multi-head structure, and KV cache.
Project category
AI Learning Project
A practical route from AI concepts to machine learning workflow, evaluation, neural networks, Python practice, handwritten digits, a CIFAR-10 CNN, adversarial traffic-defense notes, and AI security.
24 postsAI Basics Learning Roadmap
Separate AI, machine learning, and deep learning before going into implementation details.
Machine Learning Workflow
Follow the practical path from data and features to training, prediction, and evaluation.
Model Training and Evaluation
Understand loss, overfitting, train/test splits, accuracy, recall, and F1.
Neural Network Basics
Move from perceptrons to activation, forward propagation, backpropagation, and training loops.
Matrix Calculus for Neural Networks
Derive dL/dW for y = Wx + b and verify it with finite differences.
Backpropagation as a Computation Graph
Trace local gradients through ReLU and softmax cross-entropy in a two-layer MLP.
Gradient Descent and Optimizer Geometry
Compare gradient descent, momentum, and Adam on a visible quadratic loss surface.
Convolution and Receptive Field Math
Compute convolution output size, receptive fields, channel mixing, and im2col layout.
Transformer Attention Math
Hand-calculate Q/K/V scores, softmax weights, masks, multi-head structure, and KV cache.
NLP Basics: Understanding Bag of Words and TF-IDF
An introduction to the most fundamental text representation methods in NLP: Bag of Words (BoW) and TF-IDF.
RNN Basics: Handling Sequential Data with Memory
Understand the core concepts of Recurrent Neural Networks (RNN), the role of hidden states, and their application in NLP.
Transformer Self-Attention
Read Q/K/V, scaled dot-product attention, multi-head attention, and positional encoding before exploring LLM internals.
Python AI Mini Practice
Run a small scikit-learn classification task and read the experiment output.
Handwritten Digit Dataset Basics
Read train.csv, test.csv, labels, and the flattened 28 by 28 pixel layout before training the classifier.
Handwritten Digit Softmax in C
Follow the C implementation from logits and softmax probabilities to confusion matrices and submission export.
Handwritten Digit Playground Notes
See how the offline classifier was adapted into a browser demo with drawing input and probability output.
CIFAR-10 Tiny CNN Tutorial in C
Build and train a small convolutional neural network for CIFAR-10 image classification, then read its loss and accuracy output.
Building a Tiny CIFAR-10 CNN in C: Convolution, Pooling, and Backpropagation
A source-based walkthrough of cifar10_tiny_cnn.c, covering CIFAR-10 binary input, 3x3 convolution, ReLU, max pooling, fully connected logits, softmax, backpropagation, and local commands.
High-Entropy Traffic Defense Notes
Study encrypted metadata leaks, entropy, traffic classifiers, and a defensive Python chaffing prototype.
AI Security Threat Modeling
Build a defense map with NIST adversarial ML, MITRE ATLAS, and OWASP LLM risks.
Adversarial Examples and Robust Evaluation
Evaluate clean and perturbed accuracy with an FGSM-style digits experiment.
Data Poisoning and Backdoor Defense
Study poison rate, trigger behavior, attack success rate, and training pipeline controls.
Model Privacy and Extraction Defense
Measure membership inference signal and surrogate fidelity against a local toy model.
LLM, RAG, and Agent Security
Separate instructions from data and enforce tool permissions against indirect prompt injection.
Project category
Algorithm Implementation Project
Implementation-focused notes around backtracking, bit operations, clustering, code, diagrams, and downloads.
3 postsEight queens with classic backtracking
Start with state representation, conflict checks, recursive search, and the full C/Python solving flow.
Bitwise optimization for the eight queens problem
Move from array-based checks to compact bit masks so the same search becomes faster and easier to reason about.
K-means clustering on the Iris dataset in C
Study standardization, K-means++ initialization, restart selection, SSE, and the final clustering result.
Project category
Site Building Project
Notes on the bilingual site structure, content sync, categories, comments, and deployment workflow.
1 postsWelcome to haotianblog: what this bilingual technical site covers
An introduction to the bilingual site, its technical focus, and the kinds of articles and resources it will publish.