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How I Study AI - Learn AI Papers & Lectures the Easy Way

Concepts3

Groups

๐Ÿ“Linear Algebra15๐Ÿ“ˆCalculus & Differentiation10๐ŸŽฏOptimization14๐ŸŽฒProbability Theory12๐Ÿ“ŠStatistics for ML9๐Ÿ“กInformation Theory10๐Ÿ”บConvex Optimization7๐Ÿ”ขNumerical Methods6๐Ÿ•ธGraph Theory for Deep Learning6๐Ÿ”ตTopology for ML5๐ŸŒDifferential Geometry6โˆžMeasure Theory & Functional Analysis6๐ŸŽฐRandom Matrix Theory5๐ŸŒŠFourier Analysis & Signal Processing9๐ŸŽฐSampling & Monte Carlo Methods10๐Ÿง Deep Learning Theory12๐Ÿ›ก๏ธRegularization Theory11๐Ÿ‘๏ธAttention & Transformer Theory10๐ŸŽจGenerative Model Theory11๐Ÿ”ฎRepresentation Learning10๐ŸŽฎReinforcement Learning Mathematics9๐Ÿ”„Variational Methods8๐Ÿ“‰Loss Functions & Objectives10โฑ๏ธSequence & Temporal Models8๐Ÿ’ŽGeometric Deep Learning8

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๐Ÿ”ทAllโˆ‘Mathโš™๏ธAlgo๐Ÿ—‚๏ธDS๐Ÿ“šTheory

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โš™๏ธAlgorithmIntermediate

DP on Trees

DP on trees is a technique that computes answers for each node by combining results from its children using a post-order DFS.

#tree dp#post-order dfs#rerooting+12
โš™๏ธAlgorithmIntermediate

Bipartite Matching - Hopcroft-Karp

Hopcroftโ€“Karp computes maximum matching in a bipartite graph in O(E \sqrt{V}) time, which is asymptotically faster than repeated DFS (Kuhn's algorithm).

#hopcroft karp
Advanced
Filtering by:
#maximum independent set
#bipartite matching
#augmenting path
+11
โš™๏ธAlgorithmIntermediate

Flow - Modeling Techniques

Many classic problems can be modeled as a maximum flow problem by building the right network and capacities.

#max flow#dinic#bipartite matching+12