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ML

Folder: ML

143 items under this folder.

Dec 27, 2025
statistics
- folder
Dec 27, 2025
Zmniejszanie liczby przechowywanych embeddingów
Dec 27, 2025
Zero-Order Hold
Dec 27, 2025
Transformata Laplace'a
Dec 27, 2025
RL
- folder
Dec 27, 2025
Perturbation Feature Importance
Dec 27, 2025
Energy-based models
Dec 27, 2025
Inverse-propensity scoring
Dec 27, 2025
Kontroler z błędem tempa
Dec 27, 2025
DL
- folder
Dec 27, 2025
Anti-windup
Nov 27, 2025
PID controller
Oct 28, 2025
Multi-armed Bandit Problem
Oct 28, 2025
Bayesian Network
Oct 28, 2025
Contextual Multi-arm Bandit Problem
Oct 11, 2025
FTRL-Proximal
Oct 11, 2025
Random projection
Sep 23, 2025
Self attention
Sep 23, 2025
Sequence Attention Pooling
Sep 23, 2025
Shapley value
Sep 23, 2025
Sieci Neuronowe
Sep 23, 2025
Sketch
Sep 23, 2025
Softmax
Sep 23, 2025
Stable Diffusion
- generativeAI
Sep 23, 2025
Sum-product message passing
Sep 23, 2025
Temperature scaling
Sep 23, 2025
Test dokładny Fishera
Sep 23, 2025
Thermometer encoding
Sep 23, 2025
Thompson Sampling
Sep 23, 2025
Transformacja cech drzewami pod model liniowy
Sep 23, 2025
Transformer
Sep 23, 2025
UNet
Sep 23, 2025
Variable Elimination Algorithm
Sep 23, 2025
Warunek Lipschitza
Sep 23, 2025
Współczynnik korelacji liniowej
Sep 23, 2025
Zero-inflated distribution
Sep 23, 2025
Zero-shot learning
Sep 23, 2025
Zmienność sumy zmiennych losowych
Sep 23, 2025
inner-product jako miara podobieństwa i ustalenie wag
Sep 23, 2025
log-odds
Sep 23, 2025
mixup Beyond Empirical Risk Miminization
Sep 23, 2025
metryki
- folder
Sep 23, 2025
RNN
Sep 23, 2025
Randomized Response
Sep 23, 2025
Recursive Least Squares
Sep 23, 2025
Regret
Sep 23, 2025
Relative Infomation Gain
Sep 23, 2025
Rozkład Beta
Sep 23, 2025
Rozkład Laplace
Sep 23, 2025
Rozkład log-normalny
Sep 23, 2025
Rozmaitość (topologia)
Sep 23, 2025
Rozwiązanie optymalne w sensie Pareto
Sep 23, 2025
SVM
Sep 23, 2025
Scaled Dot-Product Attention
Sep 23, 2025
Normalized Binary Cross-Entropy
- metryka
Sep 23, 2025
Online Learning w Deep Learningu
Sep 23, 2025
Ordinary Linear Regression
Sep 23, 2025
Overfitting
Sep 23, 2025
Per-Coordinate Learning Rates
Sep 23, 2025
Plant
Sep 23, 2025
Policy evaluation
Sep 23, 2025
Positional Encoding
Sep 23, 2025
Quantile function
Sep 23, 2025
Quasi-identifier
Sep 23, 2025
Jak porównać dwa rozkłady?
Sep 23, 2025
Kalibracja modeli
Sep 23, 2025
Kalman filter
Sep 23, 2025
Korekcja sampling bias
Sep 23, 2025
Kowariancja
Sep 23, 2025
Kullback Leibler divergence
- metryka
Sep 23, 2025
Label Differential Privacy
Sep 23, 2025
Layer Normalization
Sep 23, 2025
Learning with Noisy Labels
Sep 23, 2025
Likelihood function
Sep 23, 2025
Linear Thompson sampling, Contextual Bandits
Sep 23, 2025
Link function
Sep 23, 2025
Liquid Neural Networks
Sep 23, 2025
Locality sensitive hashing
Sep 23, 2025
Manifold hypothesis
Sep 23, 2025
Markov Random Field
Sep 23, 2025
Markov chain
Sep 23, 2025
Maximum likelihood estimate
Sep 23, 2025
Metoda prymalno-dualna
Sep 23, 2025
Mnożniki Lagrangre'a
Sep 23, 2025
Model factorization
Sep 23, 2025
Model zwracający rozkład zamiast skalaru
Sep 23, 2025
Monte Carlo Dropout
Sep 23, 2025
Monte Carlo
Sep 23, 2025
Negative down-sampling
Sep 23, 2025
Niepewność modelu
Sep 23, 2025
Niereprodukowalność w deep learningu
Sep 23, 2025
Double ML for causal inference
Sep 23, 2025
Eksploracja
Sep 23, 2025
Embedding Binarization Problem
- hashes
Sep 23, 2025
Empirical Risk Minimization
Sep 23, 2025
Entropia binarna
Sep 23, 2025
Entropia
Sep 23, 2025
Expected Calibration Error
- metryka
Sep 23, 2025
Extreme Gradient Boosting
Sep 23, 2025
Factor graph
Sep 23, 2025
Feature importance
Sep 23, 2025
Feedback controller
Sep 23, 2025
Few-shot learning
Sep 23, 2025
Follow The Regularized Leader
Sep 23, 2025
Gaussian Belief Propagation
Sep 23, 2025
Gaussian Distribution
Sep 23, 2025
Generalized Linear Model (GLM)
Sep 23, 2025
Gower distance
Sep 23, 2025
Graphical Model
Sep 23, 2025
Grokking
Sep 23, 2025
Hierarchical clustering
Sep 23, 2025
Image representation problem
Sep 23, 2025
Image segmentation
Sep 23, 2025
Importance weighting
Sep 23, 2025
In-context learning
Sep 23, 2025
Inductive bias
Sep 23, 2025
Intrinsic dimensionality
Sep 23, 2025
Bayesian online learning probit regression
Sep 23, 2025
Belief propagation algorithm
Sep 23, 2025
Bernoulli Bandits Problem
Sep 23, 2025
Bootstrap Confidence Intervals
Sep 23, 2025
Bootstrapping jako symulacja Thompson Samplingu
Sep 23, 2025
Bootstrapping
Sep 23, 2025
CATE
Sep 23, 2025
CLIP
Sep 23, 2025
Catastrophic forgetting
Sep 23, 2025
Centralne Twierdzenie Graniczne
Sep 23, 2025
Cleora
Sep 23, 2025
Continual learning
Sep 23, 2025
Cumulative regret
Sep 23, 2025
DQN
Sep 23, 2025
Delaunay Triangulation
Sep 23, 2025
Denoising Diffusion
Sep 23, 2025
Differential Privacy
Sep 23, 2025
Differential privacy model
Sep 23, 2025
Distribution shift
Sep 23, 2025
Active learning
Sep 23, 2025
Algorytm message-passing
Sep 23, 2025
Analiza par jako wstęp do budowania klasyfikatora
Sep 23, 2025
Aproksymacja stochastyczna gradient descent
Sep 23, 2025
Balansowanie loss'ów w multi-objective problems
Sep 23, 2025
Batch Normalization
Sep 23, 2025
product limit estimation

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Folder: ML