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Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts.
Subcategories
This category has the following 34 subcategories, out of 34 total.
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B
- Bayesian networks (13 P)
- Blockmodeling (15 P)
C
- Computational learning theory (22 P)
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E
- Ensemble learning (13 P)
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- Genetic programming (14 P)
I
- Inductive logic programming (7 P)
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L
- Learning in computer vision (5 P)
- Log-linear models (2 P)
- Loss functions (11 P)
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O
R
- Reinforcement learning (12 P)
- Machine learning researchers (166 P)
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- Semisupervised learning (2 P)
- Supervised learning (5 P)
- Support vector machines (9 P)
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Pages in category "Machine learning"
The following 200 pages are in this category, out of approximately 226 total. This list may not reflect recent changes.
(previous page) (next page)A
- Accelerated Linear Algebra
- Action model learning
- Active learning (machine learning)
- Adversarial machine learning
- AIXI
- Algorithm selection
- Algorithmic bias
- Algorithmic inference
- Anomaly detection
- Aporia (company)
- Apprenticeship learning
- Artificial intelligence in hiring
- Astrostatistics
- Attention (machine learning)
- Audio inpainting
- Automated decision-making
- Automated machine learning
- Automation in construction
B
C
D
E
F
G
H
I
K
L
M
- M-theory (learning framework)
- Machine Learning (journal)
- Machine learning control
- Machine learning in bioinformatics
- Machine learning in earth sciences
- Machine learning in physics
- Machine learning in video games
- Machine-learned interatomic potential
- Manifold hypothesis
- Manifold regularization
- The Master Algorithm
- Matchbox Educable Noughts and Crosses Engine
- Matrix regularization
- Maximum inner-product search
- Meta-learning (computer science)
- MLOps
- Mountain car problem
- Multi-armed bandit
- Multi-task learning
- Multimodal sentiment analysis
- Multiple instance learning
- Multiple-instance learning
- Multiplicative weight update method
- Multitask optimization
- Multivariate adaptive regression spline
N
P
- Paraphrasing (computational linguistics)
- Parity learning
- Pattern language (formal languages)
- Pattern recognition
- Perceiver
- PHerc. Paris. 4
- Phi coefficient
- Predictive learning
- Predictive state representation
- Preference learning
- Prior knowledge for pattern recognition
- Proactive learning
- Proaftn
- Probabilistic numerics
- Probability matching
- Product of experts
- Programming by example
- Prompt engineering
- Proximal gradient methods for learning
- Pythia (machine learning)
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