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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

Level

AllBeginner
⚙️AlgorithmIntermediate

Numerical Differentiation & Finite Differences

Numerical differentiation uses finite differences to estimate derivatives when an analytical derivative is hard or impossible to obtain.

#numerical differentiation#finite differences#forward difference+12
∑MathIntermediate

Taylor Series & Approximation

Taylor series approximate a complicated function near a point by a simple polynomial built from its derivatives.

#taylor series
Intermediate
Advanced
Filtering by:
#richardson extrapolation
#taylor polynomial
#maclaurin series
+12
∑MathIntermediate

Derivatives & Differentiation Rules

Derivatives measure how fast a function changes, and rules like the product, quotient, and chain rule let us differentiate complex expressions efficiently.

#derivative#product rule#quotient rule+11
∑MathIntermediate

Limits & Continuity

A limit describes what value a function approaches as the input gets close to some point, even if the function is not defined there.

#limit#continuity#epsilon-delta+12