AI Study Notes
Concept guides on embeddings, sequence models, CNNs/ResNet, and Transformers, plus practical API setup for free LLM providers. Use the language toggle in each article header where a Chinese version exists.
Understanding Embedding
From one-hot vectors to distributed representations — Word2Vec, GloVe, and modern Transformer embeddings.
RepresentationUnderstanding LSTM Networks
Long-term dependencies, gates, and cell state in recurrent sequence models.
SequencesUnderstanding CNNs and ResNet
Convolutional blocks, residual shortcuts, and vision backbones before Transformers.
VisionUnderstanding Transformer
Attention, encoder–decoder stacks, parallelism, and complexity trade-offs.
AttentionFree LLM APIs & HackChance
OpenRouter and NVIDIA NIM free tiers and how HackChance routes between them.
Free APIOpenRouter API Key Guide
Register, create an API key, and call many models through one gateway.
GuideNVIDIA NIM API Key Guide
Generate API keys in NVIDIA Build for NIM inference endpoints.
Guide