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Concepts187

Groups

📐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

Category

🔷All∑Math⚙️Algo🗂️DS📚Theory

Level

AllBeginnerIntermediateAdvanced
⚙️AlgorithmIntermediate

Mixed Precision Training

Mixed precision training stores and computes tensors in low precision (FP16/BF16) for speed and memory savings while keeping a master copy of weights in FP32 for accurate updates.

#mixed precision#fp16#bf16+10
⚙️AlgorithmIntermediate

Distributed & Parallel Optimization

Data parallelism splits the training data across workers that compute gradients in parallel on a shared model.

#data parallelism
12345
#synchronous sgd
#asynchronous sgd
+12
⚙️AlgorithmIntermediate

Lion Optimizer

Lion (Evolved Sign Momentum) is a first-order, sign-based optimizer discovered through automated program search.

#lion optimizer#sign-based optimization#momentum+12
⚙️AlgorithmIntermediate

Sharpness-Aware Minimization (SAM)

Sharpness-Aware Minimization (SAM) trains models to perform well even when their weights are slightly perturbed, seeking flatter minima that generalize better.

#sharpness-aware minimization#sam optimizer#robust optimization+11
⚙️AlgorithmIntermediate

Sparse Matrices & Computation

A sparse matrix stores only its nonzero entries, saving huge amounts of memory when most entries are zero.

#sparse matrix#csr#csc+12
⚙️AlgorithmIntermediate

Dynamic Time Warping

Dynamic Time Warping (DTW) aligns two time series that may vary in speed to find the minimum-cost correspondence between their elements.

#dynamic time warping#dtw c++#time series alignment+11
⚙️AlgorithmAdvanced

Wake-Sleep Algorithm

The Wake–Sleep algorithm trains a pair of models: a generative model that explains how data are produced and a recognition model that guesses hidden causes from observed data.

#wake-sleep#helmholtz machine#generative model+12
⚙️AlgorithmIntermediate

Expectation Maximization (EM)

Expectation Maximization (EM) is an iterative algorithm to estimate parameters when some variables are hidden or unobserved.

#expectation maximization#em algorithm#e-step+12
⚙️AlgorithmAdvanced

Stochastic Variational Inference

Stochastic Variational Inference (SVI) scales variational inference to large datasets by taking noisy but unbiased gradient steps using minibatches.

#stochastic variational inference#elbo#variational inference+12
⚙️AlgorithmIntermediate

PPO & Trust Region Methods

Proximal Policy Optimization (PPO) stabilizes policy gradient learning by preventing each update from moving the policy too far from the previous one.

#ppo#trust region#trpo+11
⚙️AlgorithmIntermediate

Temporal Difference Learning

Temporal Difference (TD) Learning updates value estimates by bootstrapping from the next state's current estimate, enabling fast, online learning.

#temporal difference learning#td(0)#sarsa+12
⚙️AlgorithmIntermediate

t-SNE & UMAP

t-SNE and UMAP are nonlinear dimensionality-reduction methods that preserve local neighborhoods to make high-dimensional data visible in 2D or 3D.

#t-sne#umap#dimensionality reduction+12