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Concepts5

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📐Linear Algebra15📈Calculus & Differentiation10🎯Optimization14🎲Probability Theory12📊Statistics for ML9📡Information Theory10🔺Convex Optimization7🔢Numerical Methods6🕸Graph Theory for Deep Learning6🔵Topology for ML5🌐Differential Geometry6∞Measure Theory & Functional Analysis6🎰Random Matrix Theory5🌊Fourier Analysis & Signal Processing9🎰Sampling & Monte Carlo Methods10🧠Deep Learning Theory12🛡️Regularization Theory11👁️Attention & Transformer Theory10🎨Generative Model Theory11🔮Representation Learning10🎮Reinforcement Learning Mathematics9🔄Variational Methods8📉Loss Functions & Objectives10⏱️Sequence & Temporal Models8💎Geometric Deep Learning8

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🔷All∑Math⚙️Algo🗂️DS📚Theory

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AllBeginnerIntermediate
⚙️AlgorithmIntermediate

Invariant Maintenance

An invariant is a property you promise to keep true throughout an algorithm, and it is the anchor of both design and correctness proofs.

#invariant#loop invariant#search invariant+12
📚TheoryIntermediate

Amortized Analysis

Amortized analysis measures the average cost per operation over a worst-case sequence, not over random inputs.

#amortized analysis
Advanced
Filtering by:
#path compression
#aggregate method
#accounting method
+12
⚙️AlgorithmIntermediate

Minimum Spanning Tree - Kruskal

Kruskal’s algorithm builds a minimum spanning tree (MST) by sorting all edges by weight and greedily picking the next lightest edge that does not form a cycle.

#kruskal#minimum spanning tree#mst+11
🗂️Data StructureIntermediate

DSU with Weighted Edges

A DSU with weighted edges (also called a potential or difference-constraint union-find) maintains relative values between elements while still supporting near-constant-time merges and finds.

#dsu#union-find#weighted edges+11
🗂️Data StructureIntermediate

Disjoint Set Union (Union-Find)

Disjoint Set Union (Union-Find) maintains a collection of non-overlapping sets and supports fast merging and membership queries.

#disjoint set union#union-find#path compression+11