Mar 9 · 12 min read · TLDR: A hash table gives you near-O(1) lookups, inserts, and deletes by using a hash function to map keys to array indices. The tradeoff: collisions (when two keys hash to the same slot) must be handled, and a full hash table must be resized. 📖 Th...
Join discussionMar 9 · 11 min read · TLDR: Logits are the raw, unnormalized scores produced by the final layer of a neural network — before any probability transformation. Softmax converts them to probabilities. Temperature scales them before Softmax to control output randomness. 📖 T...
Join discussionMar 9 · 14 min read · TLDR: ML, Deep Learning, and LLMs are not competing technologies — they are a nested hierarchy. LLMs are a type of Deep Learning. Deep Learning is a subset of ML. Choosing the right layer depends on your data type, problem complexity, and available t...
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