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Type of stochastic recurrent neural network
A Boltzmann machine (also called Sherrington–Kirkpatrick model with external field or stochastic Ising model), named after Ludwig Boltzmann, is a spin-glass
Boltzmann_machine
Class of artificial neural network
A restricted Boltzmann machine (RBM) (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little
Restricted_Boltzmann_machine
Probability distribution of energy states of a system
In statistical mechanics and mathematics, a Boltzmann distribution (also called Gibbs distribution) is a probability distribution or probability measure
Boltzmann_distribution
Machine learning methods using multiple input modalities
descriptions. A Boltzmann machine is a type of stochastic neural network invented by Geoffrey Hinton and Terry Sejnowski in 1985. Boltzmann machines can be seen
Multimodal_learning
Interdisciplinary research area
quantum restricted Boltzmann machine. Inspired by the success of Boltzmann machines based on classical Boltzmann distribution, a new machine learning approach
Quantum_machine_learning
Subset of artificial intelligence
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn
Machine_learning
Paradigm in machine learning that uses no classification labels
dimensionality reduction techniques like principal component analysis (PCA), Boltzmann machine learning, and autoencoders. After the rise of deep learning, most
Unsupervised_learning
Branch of machine learning
nodes in deep belief networks and deep Boltzmann machines. Fundamentally, deep learning refers to a class of machine learning algorithms in which a hierarchy
Deep_learning
Dayan, Geoffrey Hinton, etc., including the Boltzmann machine, restricted Boltzmann machine, Helmholtz machine, and the wake-sleep algorithm. These were
History of artificial neural networks
History_of_artificial_neural_networks
Computational model used in machine learning
Geoffrey Hinton, and others, including the Boltzmann machine, restricted Boltzmann machine, Helmholtz machine, and the wake-sleep algorithm. These were
Neural network (machine learning)
Neural_network_(machine_learning)
Academic conference in machine learning
The International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Classification of Artificial Neural Networks (ANNs)
units). Boltzmann machine learning was at first slow to simulate, but the contrastive divergence algorithm speeds up training for Boltzmann machines and Products
Types of artificial neural networks
Types_of_artificial_neural_networks
British-Canadian computer scientist (born 1947)
knowledge and rules into AI systems. In 1985, Hinton co-invented Boltzmann machines with David Ackley and Terry Sejnowski. His other contributions to
Geoffrey_Hinton
Type of activation function
Specifically, they began by considering a single binary neuron in a Boltzmann machine that takes x {\displaystyle x} as input, and produces 1 as output
Rectified_linear_unit
brain Boltzmann constant Boltzmann distribution Boltzmann equation Quantum Boltzmann equation Boltzmann factor Boltzmann machine Deep Boltzmann machine Restricted
List of things named after Ludwig Boltzmann
List_of_things_named_after_Ludwig_Boltzmann
Technique for the generative modeling of a continuous probability distribution
\rho (x)\propto e^{-{\frac {1}{2}}\|x\|^{2}}} . This is just the Maxwell–Boltzmann distribution of particles in a potential well V ( x ) = 1 2 ‖ x ‖ 2 {\displaystyle
Diffusion_model
Machine learning technique
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence
Attention_(machine_learning)
Type of large language model
reasoning model based on the provided task. During the 2010s, improved machine learning algorithms, more powerful computers, and an increase in the amount
Generative pre-trained transformer
Generative_pre-trained_transformer
Academic conference in machine learning
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year.
International Conference on Learning Representations
International_Conference_on_Learning_Representations
Geoffrey Hinton proved a similar result about a device called a "Boltzmann machine". (Hopfield and Hinton would eventually receive the 2024 Nobel prize
History of artificial intelligence
History_of_artificial_intelligence
Overview of and topical guide to machine learning
Co-training Transduction Deep learning Deep belief networks Deep Boltzmann machines Deep Convolutional neural networks Deep Recurrent neural networks
Outline_of_machine_learning
Neural network that learns efficient data encoding in an unsupervised manner
images. In International Conference on Machine Learning (pp. 432-440). Cho, Kyunghyun (2013). "Boltzmann Machines and Denoising Autoencoders for Image Denoising"
Autoencoder
Type of artificial neural network
a composition of simple, unsupervised networks such as restricted Boltzmann machines (RBMs) or autoencoders, where each sub-network's hidden layer serves
Deep_belief_network
Set of methods for supervised statistical learning
In machine learning, a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that
Support_vector_machine
Set of learning techniques in machine learning
is the final low-dimensional feature or representation. Restricted Boltzmann machines (RBMs) are often used as a building block for multilayer learning
Feature_learning
Computer hardware technology that uses quantum mechanics
a hybrid quantum–classical generative model based on a restricted Boltzmann machine, implemented on a commercially available quantum annealing device
Quantum_computing
Type of database that uses vectors to represent other data
vectorized. These feature vectors may be computed from the raw data using machine learning methods such as feature extraction algorithms, word embeddings
Vector_database
Algorithm for modelling sequential data
Translate was revamped to Google Neural Machine Translation, which replaced the previous model based on statistical machine translation. The new model was a
Transformer_(deep_learning)
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Research field that lies at the intersection of machine learning and computer security
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques
Adversarial_machine_learning
Process of automating the application of machine learning
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of
Automated_machine_learning
Machine learning technique
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Machine learning calibration technique
In machine learning, Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution
Platt_scaling
Deep learning architecture
the most relevant expert for each token. Language modeling Transformer (machine learning model) State-space model Recurrent neural network Gu, Albert;
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Artificial intelligence algorithm
A Tsetlin machine is an artificial intelligence algorithm based on propositional logic. A Tsetlin machine is a form of learning automaton collective for
Tsetlin_machine
Smooth approximation of one-hot arg max
β = 1 / k T {\textstyle \beta =1/kT} , where k is typically 1 or the Boltzmann constant and T is the temperature. A higher temperature results in a more
Softmax_function
Tabular comparison of deep learning software
Corporation. "Restricted Boltzmann Machine with CNTK #534". GitHub, Inc. 27 May 2016. Retrieved 30 October 2023. "Multiple GPUs and machines". Microsoft Corporation
Comparison of deep learning software
Comparison_of_deep_learning_software
Type of artificial neural network
of an object within a field). Autoencoder Boltzmann machine Hopfield network Restricted Boltzmann machine Peter, Dayan; Hinton, Geoffrey E.; Neal, Radford
Helmholtz_machine
Machine learning technique
Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals instead of residuals as
Gradient_boosting
Machine-learning and computational-neuroscience conference
Information Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held annually in December
Conference on Neural Information Processing Systems
Conference_on_Neural_Information_Processing_Systems
Type of convolutional neural network
for Semantic Segmentation". IEEE Transactions on Pattern Analysis and Machine Intelligence. 39 (4): 640–651. arXiv:1411.4038. doi:10.1109/TPAMI.2016
U-Net
Reverse-engineering neural networks
identify structures, circuits or algorithms encoded in the weights of machine learning models. This contrasts with earlier interpretability methods that
Mechanistic_interpretability
Ensemble learning method
In machine learning (ML), boosting is an ensemble learning method that combines a set of less accurate models (called "weak learners") to create a single
Boosting_(machine_learning)
Conversational software
presented it more as a debunking exercise: In artificial intelligence, machines are made to behave in wondrous ways, often sufficient to dazzle even the
Chatbot
Flaw in mathematical modelling
reconstruct details of individual training instances from an overfitted machine learning model's training set. This may be undesirable if, for example
Overfitting
2018 text-generating language model
network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net
GPT-1
List of concepts in artificial intelligence
to solve the problem. Boltzmann machine A type of stochastic recurrent neural network and Markov random field. Boltzmann machines can be seen as the stochastic
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Type of feedforward neural network
(March 2003). "A neural probabilistic language model". The Journal of Machine Learning Research. 3: 1137–1155. "Papers with Code – MLP-Mixer: An all-MLP
Multilayer_perceptron
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
AI platform developed by IBM
network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net
IBM_Watsonx
AI that learns decision rules from data
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves
Rule-based_machine_learning
Statistics and machine learning technique
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from
Ensemble_learning
Type of feedforward neural network
features have been introduced, based on convolutional gated restricted Boltzmann machines and independent subspace analysis. Its application can be seen in
Convolutional_neural_network
Machine learning model training problem
layers of binary or real-valued latent variables. It uses a restricted Boltzmann machine to model each new layer of higher level features. Each new layer guarantees
Vanishing_gradient_problem
American linguist
formalism for artificial neural networks that introduced the restricted Boltzmann machine architecture. This work, up through the early 2000s, is presented
Paul_Smolensky
2023 text-generating language model
network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net
IBM_Granite
Type of machine learning model
1990s, IBM's statistical models pioneered word alignment techniques for machine translation, laying the groundwork for corpus-based language modeling.
Large_language_model
Automated recognition of patterns and regularities in data
While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities but their primary function is to
Pattern_recognition
Deep learning method
pass, rather than multiple passes through the network. Compared to Boltzmann machines and linear ICA, there is no restriction on the type of function used
Generative adversarial network
Generative_adversarial_network
Academic journal
The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the
Journal of Machine Learning Research
Journal_of_Machine_Learning_Research
Method used to normalize the range of independent variables
preprocessing step. Since the range of values of raw data varies widely, in some machine learning algorithms, objective functions will not work properly without
Feature_scaling
American neuroscientist (born 1947)
biology, physics, mathematics, and engineering. He co-invented the Boltzmann machine with Geoffrey Hinton and pioneered the application of learning algorithms
Terry_Sejnowski
Integrated circuit technology
the creation of neuristors that mimic neuron behavior and support Turing machine components. Also in 2012, Purdue University researchers presented a neuromorphic
Neuromorphic_computing
Artificial neural network node function
on Machine Learning. PMLR: 1329–1338. arXiv:1803.01206. Nair, Vinod; Hinton, Geoffrey E. (2010), "Rectified Linear Units Improve Restricted Boltzmann Machines"
Activation_function
Approach in generative models
functions of which are parameterized by modern deep neural networks. Boltzmann machines are a special form of energy-based models with a specific parametrization
Energy-based_model
Use of machine learning to rank items
Learning to rank (LTR) or machine-learned ranking (MLR) is the application of machine learning, often supervised, semi-supervised or reinforcement learning
Learning_to_rank
American computer scientist (born 1948)
titled as "Massively Parallel Architectures for AI: NETL, Thistle and Boltzmann Machines". Fahlman was not the first to suggest the concept of the emoticon
Scott_Fahlman
Vector quantization algorithm minimizing the sum of squared deviations
sophisticated feature learning approaches such as autoencoders and restricted Boltzmann machines. However, it generally requires more data, for equivalent performance
K-means_clustering
Similarity measure for number sequences
network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net
Cosine_similarity
Type of artificial neural network
Extreme learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning
Extreme_learning_machine
Extracting features from raw data for machine learning
Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set
Feature_engineering
Machine learning technique
In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization
Normalization (machine learning)
Normalization_(machine_learning)
Deep learning library
Institute. It was a machine-learning library written in C++ and CUDA, supporting methods including neural networks, support vector machines (SVM), hidden Markov
PyTorch
Specific probability distribution function, important in physics
Maxwell–Boltzmann distribution, or Maxwell(ian) distribution, is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann.
Maxwell–Boltzmann distribution
Maxwell–Boltzmann_distribution
Models used to produce word embeddings
gene sequences, this representation can be widely used in applications of machine learning in proteomics and genomics. The results suggest that BioVectors
Word2vec
2019 text-generating language model
exaggerated; Anima Anandkumar, a professor at Caltech and director of machine learning research at Nvidia, said that there was no evidence that GPT-2
GPT-2
Class of algorithms for pattern analysis
In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These
Kernel_method
Plot of machine learning model performance over time or experience
In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and
Learning curve (machine learning)
Learning_curve_(machine_learning)
Probabilistic model
discriminative model specified over an undirected graph. A restricted Boltzmann machine is a bipartite generative model specified over an undirected graph
Graphical_model
Machine learning software library
TensorFlow is a software library for machine learning and artificial intelligence. It can be used across a range of tasks, but is used mainly for training
TensorFlow
2025 multimodal model by OpenAI
network Recurrent neural network LSTM GRU ESN reservoir computing Boltzmann machine Restricted GAN Diffusion model SOM Convolutional neural network U-Net
GPT-5
Concept in machine learning
on Machine Learning. Memisevic, Roland; Hinton, Geoffrey (2010). "Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines"
Tensor_(machine_learning)
Machine learning software library
MindSpore is an open-source software framework for deep learning, machine learning and artificial intelligence developed by Huawei. MindSpore provides
MindSpore
Field of machine learning
In machine learning and optimal control, reinforcement learning (RL) is concerned with how an intelligent agent should take actions in a dynamic environment
Reinforcement_learning
Machine learning technique
Mixture of experts (MoE) is a machine learning technique where multiple expert networks (learners) are used to divide a problem space into homogeneous
Mixture_of_experts
Open-source deep learning library
machine (JVM). It is a framework with wide support for deep learning algorithms. Deeplearning4j includes implementations of the restricted Boltzmann machine
Deeplearning4j
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals
Self-supervised_learning
Recurrent neural network architecture
classification, data processing, time series analysis tasks, speech recognition, machine translation, speech activity detection, robot control, video games, healthcare
Long_short-term_memory
Software user interface
the context of machine learning.It is also used in conversational AI to manage complex interactions that require human empathy. In machine learning, HITL
Human-in-the-loop
Software program
research group out of the University of Sussex created a Hallucination Machine, applying the DeepDream algorithm to a pre-recorded panoramic video, allowing
DeepDream
Canadian physicist and entrepreneur
University of Waterloo. Retrieved June 5, 2024. "Quantum Approximate Boltzmann Machines - Guillaume Verdon". Research Institute for Advanced Computer Science
Guillaume_Verdon
Technique in machine learning
Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"
Curriculum_learning
used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Machine learning technique
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related
Transfer_learning
Deep learning generative model to encode data representation
In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling in
Variational_autoencoder
Optimization algorithm
has become an important optimization method in machine learning. Both statistical estimation and machine learning consider the problem of minimizing an
Stochastic_gradient_descent
Model-free reinforcement learning algorithm
reinforcement learning" (PDF). 2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE. pp. 173–178. doi:10.1109/SAMI
Q-learning
Numerical method that reduces the complexity of computationally intensive simulations
surrogate model; to this end, the method is also associated with the field of machine learning. The main use of POD is to decompose a physical field (like pressure
Proper orthogonal decomposition
Proper_orthogonal_decomposition
Experience of hallucinations by blind people
maintain visual acuity may still be susceptible to CBS. The Deep Boltzmann Machine (DBM) is a way of utilizing an undirected probabilistic process in
Visual_release_hallucinations
Difficulties arising when analyzing data with many aspects ("dimensions")
occur in domains such as numerical analysis, sampling, combinatorics, machine learning, data mining and databases. The common theme of these problems
Curse_of_dimensionality
BOLTZMANN MACHINE
BOLTZMANN MACHINE
Surname or Lastname
English (chiefly Kent and Sussex)
English (chiefly Kent and Sussex) : occupational name for a designer or engineer, from a Middle English reduced form of Old French engineor ‘contriver’ (a derivative of engaigne ‘cunning’, ‘ingenuity’, ‘stratagem’, ‘device’). Engineers in the Middle Ages were primarily designers and builders of military machines, although in peacetime they might turn their hands to architecture and other more pacific functions.German : from the Latin personal name Januarius (see January 1). Jänner is a South German word for ‘January’, and so it is possible that this is one of the surnames acquired from words denoting months of the year, for example by converts who had been baptized in that month, people who were born or baptized in that month, or people whose taxes were due in January.
Surname or Lastname
English
English : variant of Bulman.Altered spelling of German Bollmann or Bullmann, a variant of Bull 2.
Surname or Lastname
English, Scottish, and northern Irish
English, Scottish, and northern Irish : occupational name for a maker of machinery, mostly in wood, of any of a wide range of kinds, from Old English wyrhta, wryhta ‘craftsman’ (a derivative of wyrcan ‘to work or make’). The term is found in various combinations (for example, Cartwright and Wainwright), but when used in isolation it generally referred to a builder of windmills or watermills.Common New England Americanized form of French Le Droit, a nickname for an upright person, a man of probity, from Old French droit ‘right’, in which there has been confusion between the homophones right and wright.
Boy/Male
American, Australian
Weighing Machine
Surname or Lastname
English
English : in part probably a metonymic occupational name for a soldier in charge of a catapult- or bow-like machine used for throwing heavy missiles, Old French espringalle, Anglo-French springalde. However, Reaney and Wilson, believe the Middle English word springal(d) (which appears to have contributed to the surname), to have a different derivation, perhaps a nickname for a young man, a stripling, from spring (see Spring).
Surname or Lastname
Jewish (Ashkenazic)
Jewish (Ashkenazic) : occupational name for a cantor in a synagogue, from Yiddish zinger ‘singer’.English : variant of Sanger 2, in fact a Middle English recoinage from the verb sing(en) ‘to sing’.German : variant of Sänger (see Sanger 1) in the sense of ‘poet’.Isaac Merrit Singer, inventor of the eponymous sewing machine, was born in 1811 in Pittstown, NY, the son of German immigrant Adam Reisinger. He had five wives and fathered 24 children. Singer, who incorporated his company as the Singer Manufacturing Company in 1864, left a fortune worth $13 million to his various heirs.
Girl/Female
Bengali, Indian
Machine
Surname or Lastname
English and French
English and French : metonymic occupational name, from Middle English, Old French trone ‘weighing machine’.
BOLTZMANN MACHINE
BOLTZMANN MACHINE
Girl/Female
Indian
The quiet one
Boy/Male
Indian, Kashmiri
Affection
Girl/Female
Australian, Christian, French, German, Latin, Shakespearean
The Lost
Girl/Female
French, German, Hebrew
The Perfect One; Sea of Bitterness; Sea of Sorrow; Wished for Child; Rebellious; Star; Similar to Mary
Girl/Female
Hindu, Indian, Tamil
Pomegranate Blossom
Boy/Male
Muslim
The prophet
Girl/Female
Tamil
A flower
Biblical
eloquent
Male
Hebrew
(×ï‹×žÖ¸×¨) Hebrew name OWMAR means "eloquent, talkative" or "speaker." In the bible, this is the name of a grandson of Esau.
Boy/Male
Biblical
Raised; who pardons.
BOLTZMANN MACHINE
BOLTZMANN MACHINE
BOLTZMANN MACHINE
BOLTZMANN MACHINE
BOLTZMANN MACHINE
n.
A machine for cleansing or loosening wool by the action of a revolving cylinder covered with long iron spikes or teeth; a willy or willying machine; -- called also twilly devil, and devil. See Devil, n., 6, and Willy.
n.
A funnel, or short, fiaring pipe, used as a guide or conductor, as for yarn in a knitting machine.
v. t.
To subject to the action of machinery; to effect by aid of machinery; to print with a printing machine.
n.
A combination of persons acting together for a common purpose, with the agencies which they use; as, the social machine.
a.
Adapted or adaptable to all or to various uses, shapes, sizes, etc.; as, a universal milling machine.
v. t.
The act of employing anything, or of applying it to one's service; the state of being so employed or applied; application; employment; conversion to some purpose; as, the use of a pen in writing; his machines are in general use.
n.
One who or operates a machine; a machinist.
v. t.
To make useful; to turn to profitable account or use; to make use of; as, to utilize the whole power of a machine; to utilize one's opportunities.
n.
A machine for concentrating ore. See Frue vanner.
n.
In general, any combination of bodies so connected that their relative motions are constrained, and by means of which force and motion may be transmitted and modified, as a screw and its nut, or a lever arranged to turn about a fulcrum or a pulley about its pivot, etc.; especially, a construction, more or less complex, consisting of a combination of moving parts, or simple mechanical elements, as wheels, levers, cams, etc., with their supports and connecting framework, calculated to constitute a prime mover, or to receive force and motion from a prime mover or from another machine, and transmit, modify, and apply them to the production of some desired mechanical effect or work, as weaving by a loom, or the excitation of electricity by an electrical machine.
n.
An apparatus for measuring speed, as of machinery or vessels, but especially of projectiles.
n.
A contrivance for effecting ventilation; especially, a contrivance or machine for drawing off or expelling foul or stagnant air from any place or apartment, or for introducing that which is fresh and pure.
n.
A joint or other connection uniting parts of machinery, or the like, as the elastic pipe of a tender connecting it with the feed pipe of a locomotive engine; especially, a pipe fitting for connecting pipes, or pipes and fittings, in such a way as to facilitate disconnection.
n.
Machines, in general, or collectively.
n.
A form of weighing machine for heavy wares, consisting of two horizontal bars crossing each other, beaked at the extremities, and supported by a wooden pillar. It is now mostly disused.
n.
One who, or that which, sets type; a compositor; a machine for setting type.
n.
The working parts of a machine, engine, or instrument; as, the machinery of a watch.
imp. & p. p.
of Machine