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Deep learning model structure
A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and
Layer_(deep_learning)
Branch of machine learning
layers help in learning the features effectively. Deep learning architectures can be constructed with a greedy layer-by-layer method. Deep learning helps
Deep_learning
Machine learning technique
In deep learning, fine-tuning is the process of adapting a computational model trained for one task (the upstream task) to perform a different, usually
Fine-tuning_(deep_learning)
Overview of and topical guide to deep learning
provided as an overview of, and topical guide to, deep learning: Deep learning is a subfield of machine learning and artificial intelligence based on artificial
Outline_of_deep_learning
Algorithm for modelling sequential data
In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is
Transformer_(deep_learning)
Computational model used in machine learning
multiple intermediate layers (hidden layers). A network is typically called a deep neural network if it has at least two hidden layers. Deep neural networks
Neural network (machine learning)
Neural_network_(machine_learning)
Type of feedforward neural network
In deep learning, a multilayer perceptron (MLP) is a kind of modern feedforward neural network consisting of fully connected neurons with nonlinear activation
Multilayer_perceptron
Type of feedforward neural network
that learns features via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different
Convolutional_neural_network
Paradigm in machine learning that uses no classification labels
(PCA), Boltzmann machine learning, and autoencoders. After the rise of deep learning, most large-scale unsupervised learning has been done by training
Unsupervised_learning
Type of layer in artificial neural networks
artificial neural networks, a hidden layer is a layer of artificial neurons that is neither an input layer nor an output layer. The simplest examples appear
Hidden_layer
Type of artificial neural network
Handling, the first working deep learning algorithm, a method to train arbitrarily deep neural networks. It is based on layer by layer training through regression
Feedforward_neural_network
Machine learning that combines deep learning and reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the
Deep_reinforcement_learning
Machine learning technique
the attention maps with respect to any attention head at any layer, while the deeper layers tend to show more semantically meaningful visualization. Attention
Attention_(machine_learning)
Topics referred to by the same term
browsers Layer of objects, a term in CAD Map layer, a set of graphical information, especially in geographic information systems Layer (deep learning), a structure
Layer
Type of artificial neural network
learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of
Deep_belief_network
Deep learning architecture
Mamba is a deep learning architecture focused on sequence modeling. It was developed by two researchers Albert Gu from Carnegie Mellon University and
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Type of artificial neural network
network or ResNet) is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed
Residual_neural_network
Neural network technology
2017, as networks grew increasingly deep. Convolutional neural network Pooling layer Feature learning Deep learning Computer vision Goodfellow, Ian; Bengio
Convolutional_layer
Subset of artificial intelligence
in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance
Machine_learning
Research field in deep learning
Topological deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models
Topological_deep_learning
Parameter-efficient fine-tuning technique for large language models
to 350 gigabytes). The technique applies broadly to any dense layers in deep learning models, though it has been most extensively studied in the context
LoRA_(machine_learning)
Type of activation function
Tobit model Layer (deep learning) Brownlee, Jason (8 January 2019). "A Gentle Introduction to the Rectified Linear Unit (ReLU)". Machine Learning Mastery
Rectified_linear_unit
Machine learning methods using multiple input modalities
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images
Multimodal_learning
Family of convolutional neural networks
license on GitHub. The Inception v1 architecture is a deep CNN composed of 22 layers. Most of these layers were "Inception modules". The original paper stated
Inception (deep learning architecture)
Inception_(deep_learning_architecture)
Machine learning technique
Conference on Machine Learning. PMLR: 794–803. arXiv:1711.02257. "Normalization Layers". labml.ai Deep Learning Paper Implementations. Retrieved 2024-08-07.
Normalization (machine learning)
Normalization_(machine_learning)
Class of artificial neural networks
passing" for such approaches. In the more general subject of "geometric deep learning", certain existing neural network architectures can be interpreted as
Graph_neural_network
Machine learning technique
paper that applies MoE to deep learning dates back to 2013, which proposed to use a different gating network at each layer in a deep neural network. Specifically
Mixture_of_experts
Set of learning techniques in machine learning
different factors on multiple levels. In a deep learning architecture, the output of each intermediate layer can be viewed as a representation of the original
Feature_learning
Technique for setting initial values of trainable parameters in a neural network
In deep learning, weight initialization or parameter initialization describes the initial step in creating a neural network. A neural network contains
Weight_initialization
Software program
(2009). Visualizing Higher-Layer Features of a Deep Network. International Conference on Machine Learning Workshop on Learning Feature Hierarchies. S2CID 15127402
DeepDream
Structure at the rear of the vertebrate brain, beneath the cerebrum
consists of a tightly folded layer of cortex, with white matter underneath and a fluid-filled ventricle at the base. Four deep cerebellar nuclei are embedded
Cerebellum
A 1971 paper described a deep network with the equivalent of eight layers trained by this method. The first deep learning multilayer perceptron trained
History of artificial neural networks
History_of_artificial_neural_networks
Chinese artificial intelligence company
capabilities. DeepSeek significantly reduced training expenses for their R1 model by incorporating techniques such as mixture of experts (MoE) layers. The company
DeepSeek
Classification of Artificial Neural Networks (ANNs)
It uses a deep multilayer perceptron with eight layers. It is a supervised learning network that grows layer by layer, where each layer is trained by
Types of artificial neural networks
Types_of_artificial_neural_networks
Neural network that learns efficient data encoding in an unsupervised manner
Dimensionality reduction was one of the first deep learning applications. For Hinton's 2006 study, he pretrained a multi-layer autoencoder with a stack of RBMs and
Autoencoder
Model-free reinforcement learning algorithm
"deep Q-learning," that can play Atari 2600 games at expert human levels. The DeepMind system used a deep convolutional neural network, with layers of tiled
Q-learning
Software tool
Deep Learning Studio is a software tool that aims to simplify the creation of deep learning models used in artificial intelligence. It is compatible with
Deep_Learning_Studio
Concept in machine learning
embeddings, the connection of tensor layers, and the operations performed on them in a network. Modern machine learning frameworks manage the optimization
Tensor_(machine_learning)
Structure in biology and artificial intelligence
dataset. The term deep neural network refers to neural networks that have more than three layers, typically including at least two hidden layers in addition
Neural_network
Feature of artificial neural networks
models used in machine learning, and inspired by biological neural networks. They are the core component of modern deep learning algorithms. Computation
Large width limits of neural networks
Large_width_limits_of_neural_networks
Explainable AI technique
increasingly abstract features through multiple layers. CNNs are a specific architecture of deep learning models, designed to process spatially structured
Class_activation_mapping
Machine learning model for vision processing
exaFLOPs. Transformer (machine learning model) Convolutional neural network Attention (machine learning) Perceiver Deep learning PyTorch TensorFlow All positional
Vision_transformer
Deep learning library
PyTorch is an open-source deep learning library, originally developed by Meta Platforms and currently developed with support from the Linux Foundation
PyTorch
Method of speech synthesis that uses deep neural networks
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech)
Deep learning speech synthesis
Deep_learning_speech_synthesis
Distribution over functions corresponding to an infinitely wide Bayesian neural network
who worked in Bayesian learning. Today the correspondence is proven for: Single hidden layer Bayesian neural networks; deep fully connected networks
Neural network Gaussian process
Neural_network_Gaussian_process
Influential 2012 deep convolutional neural network
in deep learning, especially in applying neural networks to computer vision. AlexNet contains eight layers: the first five are convolutional layers, some
AlexNet
Open-source deep learning library
TensorFlow, Keras and other deep learning libraries in an enterprise distribution called the Skymind Intelligence Layer. Deeplearning4j was contributed
Deeplearning4j
Sub-field of reinforcement learning
autocurricula. As the agents' policy is improved using self-play, multiple layers of learning may occur. MARL is used to explore how separate agents with identical
Multi-agent reinforcement learning
Multi-agent_reinforcement_learning
Class of artificial neural network
history compressor system solved a "Very Deep Learning" task that required more than 1000 subsequent layers in an RNN unfolded in time. Long short-term
Recurrent_neural_network
Architectural motif in neural networks for aggregating information
In neural networks, a pooling layer is a kind of network layer that downsamples and aggregates information that is dispersed among many vectors into fewer
Pooling_layer
Software for understanding biological data
structure prediction, this proved difficult. Machine learning techniques such as deep learning can learn features of data sets rather than requiring
Machine learning in bioinformatics
Machine_learning_in_bioinformatics
Optimization algorithm for artificial neural networks
learning algorithm was gradient descent with a squared error loss for a single layer. The first multilayer perceptron (MLP) with more than one layer trained
Backpropagation
and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Type of artificial neural network
In machine learning, the Highway Network was the first working very deep feedforward neural network with hundreds of layers, much deeper than previous
Highway_network
types addressed by deep learning in PAM are displacements in the vertical and tilted directions. Chen et al. used a simple three layer convolutional neural
Deep learning in photoacoustic imaging
Deep_learning_in_photoacoustic_imaging
Deep learning artificial intelligence research team
Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the
Google_Brain
Parameter controlling the machine learning process
Reproducibility can be particularly difficult for deep learning models. For example, research has shown that deep learning models depend very heavily even on the
Hyperparameter (machine learning)
Hyperparameter_(machine_learning)
Machine learning model training problem
In machine learning, the vanishing gradient problem is the problem of greatly diverging gradient magnitudes between earlier and later layers encountered
Vanishing_gradient_problem
Artificial intelligence program by DeepMind
program developed by DeepMind, a subsidiary of Alphabet, which performs predictions of protein structure. It is designed using deep learning techniques. AlphaFold
AlphaFold
1998 film by Mimi Leder
one Russian cosmonaut. They land on the outer-most layer of the comet, and drill the nuclear bombs deep beneath its surface, but it shifts into the sunlight
Deep_Impact_(film)
Interdisciplinary research area
applicable to classical deep learning and vice versa. Furthermore, researchers investigate more abstract notions of learning theory with respect to quantum
Quantum_machine_learning
Biological theory of intelligence
which leads to greater temporal stability seen by the parent layer. Cortical learning algorithms are able to learn continuously from each new input pattern
Hierarchical_temporal_memory
Decentralized machine learning
things, and pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets
Federated_learning
science, a convolutional deep belief network (CDBN) is a type of deep artificial neural network composed of multiple layers of convolutional restricted
Convolutional deep belief network
Convolutional_deep_belief_network
Series of convolutional neural networks for image classification
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (2016). "Deep Residual Learning for Image Recognition". 2016 IEEE Conference on Computer Vision
VGGNet
Artificial neural network node function
for Deep Learning". arXiv:1811.03378 [cs.LG]. Dubey, Shiv Ram; Singh, Satish Kumar; Chaudhuri, Bidyut Baran (2022). "Activation functions in deep learning:
Activation_function
Property of artificial neural networks
Michael A. (2015). Neural Networks and Deep Learning. G. Cybenko, "Continuous Valued Neural Networks with Two Hidden Layers are Sufficient", Technical Report
Universal approximation theorem
Universal_approximation_theorem
Type of stochastic recurrent neural network
possible to train many layers of hidden units efficiently and is one of the most common deep learning strategies. As each new layer is added the generative
Boltzmann_machine
Diffusion model over latent embedding space
(2015-06-01). "Deep Unsupervised Learning using Nonequilibrium Thermodynamics" (PDF). Proceedings of the 32nd International Conference on Machine Learning. 37.
Latent_diffusion_model
System of building very large integrated circuit networks
notably massively parallel supercomputers, but is now being employed for deep learning. The name is taken from the term very-large-scale integration, the state
Wafer-scale_integration
Algorithm for supervised learning of binary classifiers
layer (also called a single-layer perceptron). Single-layer perceptrons are only capable of learning linearly separable patterns. For a classification task
Perceptron
Open standard for parallel computing
spans several domains, including libraries for linear algebra, deep learning, machine learning, video processing, and others. The source code of parts of
OneAPI_(compute_acceleration)
Intelligence of machines
transmitted to the next layer. A network is typically called a deep neural network if it has at least 2 hidden layers. Learning algorithms for neural networks
Artificial_intelligence
British-Canadian computer scientist (born 1947)
multi-layer neural networks, although they were not the first to propose the approach. Hinton is viewed as a leading figure in the deep learning community
Geoffrey_Hinton
Type of artificial neural network
hidden layer with randomized weights that did not learn, and a learning output layer. According to some researchers, these models are able to produce
Extreme_learning_machine
Machine learning technique
fully-connected layers to improve performance. Crossover (genetic algorithm) Domain adaptation General game playing Multi-task learning Multitask optimization
Transfer_learning
Method of improving artificial neural network
initialization and changes in the distribution of the inputs of each layer affect the learning rate of the network. However, newer research suggests it doesn’t
Batch_normalization
Overview of and topical guide to machine learning
Comparison of machine learning software Comparison of deep learning software Amazon Machine Learning Microsoft Azure Machine Learning Studio DistBelief (replaced
Outline_of_machine_learning
tasks. Deep learning uses multiple layers of ANN and other techniques to progressively extract information from an input. Due to this complex layered approach
Machine learning in video games
Machine_learning_in_video_games
Reinforcement learning method
error-driven learning, the significance of NER is quite profound. Traditional sequence labeling methods identify nested entities layer by layer. If an error
Error-driven_learning
Canadian computer scientist
scientist most noted for his work on artificial neural networks and deep learning. In 2012, Krizhevsky, Ilya Sutskever and their PhD advisor Geoffrey
Alex_Krizhevsky
Software company
specializes in developing natural-sounding speech synthesis software using deep learning. The name ElevenLabs derives from the English word eleven. The number
ElevenLabs
Neural network library
training of deep-learning models on clusters of graphics processing units (GPU) and tensor processing units (TPU). Comparison of deep-learning software "Release
Keras
Type of machine learning model
McCallum, Andrew (28 July 2019). "Energy and Policy Considerations for Deep Learning in NLP" (PDF). ACL Anthology. Retrieved 2 October 2025. He, Yuhao; Yang
Large_language_model
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 method to transfer knowledge from a large model to a smaller one
Alexey Ivakhnenko and Valentin Lapa in USSR (1965). Their deep networks were trained layer by layer through regression analysis. Superfluous hidden units
Knowledge_distillation
Methods in artificial intelligence research
increase the power of neural networks." Over the next several years, deep learning had spectacular success in handling vision, speech recognition, speech
Symbolic artificial intelligence
Symbolic_artificial_intelligence
Framework for communication protocols used in IP networking
the layers are the link layer, containing communication methods for data that remains within a single network segment (link); the internet layer, providing
Internet_protocol_suite
Machine learning framework
Neural operators are a class of deep learning architectures designed to learn maps between infinite-dimensional function spaces. Neural operators represent
Neural_operators
Techniques for lossy compression of neural networks
Carreira-Perpiñán, Miguel Á. (2020). "Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer". 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Model_compression
Convolutional neural network structure
neural networks and was historically important during the development of deep learning. In general, when LeNet is referred to without a number, it refers to
LeNet
Interpretable computational sub-graphs within artificial neural networks
mechanistic interpretability. Researchers aim to reverse-engineer "black box" deep learning models by identifying their fundamental variables – known as features
Circuit_(neural_network)
Outermost layer of the epidermis
The stratum corneum (Latin for 'horned/horny layer') is the outermost layer of the epidermis of the tetrapod skin. In human skin, it consists of a stratified
Stratum_corneum
AI's tendency to abruptly and drastically forget old info after learning new info
layer is identical to the input pattern. McRae and Hetherington (1993) argued that humans, unlike most neural networks, do not take on new learning tasks
Catastrophic_interference
Image-generating machine learning model
Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology
Stable_Diffusion
Type of artificial neural network architecture
for MLP layers. Despite KANs' general-purpose design, researchers have created and used them for a number of tasks: Scientific machine learning (SciML):
Kolmogorov–Arnold_Networks
Recurrent neural network architecture
Transformers scale better than LSTM on text data. Attention (machine learning) Deep learning Differentiable neural computer Gated recurrent unit Highway network
Long_short-term_memory
2020 text-generating language model
transformer-based deep-learning neural network architectures. Previously, the best-performing neural NLP models commonly employed supervised learning from large
GPT-3
membrane zone), and the superficial layer of the lamina propria. The transition is composed of the intermediate and deep layers of the lamina propria. The body
Histology_of_the_vocal_cords
Series of language models developed by Google AI
(2024). "11.9. Large-Scale Pretraining with Transformers". Dive into deep learning. Cambridge New York Port Melbourne New Delhi Singapore: Cambridge University
BERT_(language_model)
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
Surname or Lastname
English (Sussex and Kent)
English (Sussex and Kent) : topographic name for someone who lived by a stream, from Old English lacu ‘stream’ (see Lake) + the suffix -er denoting an inhabitant.
Girl/Female
Hindu
The wave
Surname or Lastname
Indian (northern states)
Indian (northern states) : Hindu name meaning ‘lamp’, from Sanskrit dīpa. It occurs commonly as the final element of compound personal names, e.g. in Kuldeep ‘light of the family’. Subsequently, it appears to have evolved into a surname.English : presumably from the adjective deep, either a topographic name for someone who lived in a deep valley, or perhaps a nickname for a ‘deep’, thoughtful person.
Boy/Male
Assamese, Bengali, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Oriya, Punjabi, Sanskrit, Sikh, Sindhi, Tamil, Telugu, Traditional
Superior to Infinity; A Lamp
Surname or Lastname
English
English : variant spelling of Dear.Scottish : habitational name from (Old and New) Deer in Aberdeenshire.Hungarian : variant of Dér, from the secular personal name.
Surname or Lastname
English
English : occupational name for a washerman, Anglo-Norman French laver (an agent derivative of Old French laver ‘to wash’, Latin lavare).English : habitational name from High, Little or Magdalen Laver in Essex, named from Old English lagu ‘flood’, ‘water’ + fær ‘passage’, ‘crossing’.English : topographic name for someone living where bulrushes or irises grew, Old English lǣfer.
Surname or Lastname
English
English : occupational name for a maker of cord and string, derived from Middle English lace ‘cord’ (Old French laz, las).
Surname or Lastname
English
English : status name for a mayor, Middle English, Old French mair(e) (from Latin maior ‘greater’, ‘superior’; compare Mayor). In France the title denoted various minor local officials, and the same is true of Scotland (see Mair 1). In England, however, the term was normally restricted to the chief officer of a borough, and the surname may have been given not only to a citizen of some standing who had held this office, but also as a nickname to a pompous or officious person.German and Dutch : variant of Meyer 1.Jewish (Ashkenazic) : variant of Meyer 2.
Surname or Lastname
English
English : variant of Ayer.English : topographic name for someone who lived by an enclosure, Middle English hay (see Hay 1) + the suffix -er(e) denoting an inhabitant.French : occupational name for a warder of woodland, from an agent derivative of Old French haye ‘hedge’, ‘enclosed forest’.South German : from an agent derivative of Middle High German heien ‘to guard or protect’, hence an occupational name for a warden of woodland or crops.Indian (Panjab) : Sikh name based on the name of a Jat clan, also called Her.
Surname or Lastname
English
English : from the Norman personal name Raher, composed of the Germanic elements rad ‘counsel’, ‘advice’ + hari, heri ‘army’.French : occupational name for a barber, Old French raier (from rère ‘to shave’).
Surname or Lastname
English
English : from the Middle English personal name Saher or Seir. This is probably a Norman introduction of the Continental Germanic personal name Sigiheri, composed of the elements sigi ‘victory’ + heri ‘army’. However, it could also represent a Middle English survival of an unrecorded Old English name, SÇ£here, composed of the elements sÇ£ ‘sea’ + here ‘army’.English : occupational name, from Middle English saghier (see Sawyer) or Old French seieor.English : occupational name for a professional reciter, from an agent derivative of Middle English say(en), sey(en) ‘to say’.English : from a reduced form of Middle English assayer, an agent derivative of assay ‘trial’, ‘test’, Old French essay (from Late Latin exagium, a derivative of exagminÄre ‘to weigh’), hence an occupational name for an assayer of metals or a taster of food.English : occupational name for a maker or seller of say, a type of cloth, from Middle English say + the agent suffix -er. See also Say.Welsh : occupational name from Welsh saer ‘carpenter’ or from saer maen ‘stonecutter’, i.e. mason.French : occupational name for a reaper or mower, from an agent derivative of Old French seer ‘to cut’ (Latin secare).Dutch : occupational name for a weaver of serge, from an agent derivative of saai ‘serge’.Dutch : occupational name from zaaier ‘sower’.
Surname or Lastname
English and Irish
English and Irish : variant of Dean.Dutch : ethnic name for a Dane, Middle Dutch Deen.
Surname or Lastname
English
English : from an agent derivative of Middle English pleyen ‘to play’, hence an occupational name for an actor or musician or a nickname for a successful competitor in contests of athletic or sporting prowess.
Surname or Lastname
English
English : habitational name from any of three places in Essex – Layer Breton, Layer de la Haye, and Layer Marney – all named from a river name, Leire, or from Leire in Leicestershire, also named from an identical river name. The river name is of Celtic origin and is probably the base of the tribal name Ligore, found in the place name Leicester.English : nickname or status name from Anglo-Norman French le eyr ‘the heir’. Compare Ayer.English : occupational name for a stone layer, Middle English leyer; the job of the layer was to position the stones worked by the masons.German : habitational name for someone from any of the various placed named Lay, in the Rhineland and Bavaria.
Surname or Lastname
Jewish (eastern Ashkenazic)
Jewish (eastern Ashkenazic) : ornamental name from Yiddish fayer ‘fire’ or Yiddishized form of Feuer.English : variant of Fair.
Male
Yiddish
(לֵייזֶער) Yiddish form of Hebrew Elazar, LAZER means "my God has helped."
Boy/Male
Indian
Tourist, Who visits holy places
Boy/Male
Hindu
A lamp, Beautiful
Girl/Female
Indian, Punjabi, Sikh
The Lamp of Light
Male
English
English unisex short form of longer names beginning with the letter "D." In some cases, it may be of Scottish origin, associated with the River Dee, possibly DEE means "dark water." Compare with strictly feminine Dee.
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
Male
Polish
 Polish form of Greek Stephanos, STEFAN means "crown." Compare with other forms of Stefan.
Female
Serbian
(Дијана) Serbian form of Latin Diana, DIJANA means "divine, heavenly."
Boy/Male
Muslim/Islamic
Delicacy
Boy/Male
Basque, Biblical, French, German, Hebrew
A Flock; Herd
Boy/Male
Assamese, Hindu, Indian, Punjabi, Sikh
Bright; Clean; Lovely Bright
Boy/Male
Arabic, Modern
Grape
Boy/Male
Muslim
Supported
Boy/Male
Indian
Inevitable, Lion, Powerful
Girl/Female
Tamil
Victorious, Victory
Boy/Male
French
The father is peace, or father of peace. Form of Hebrew Absolom who was son of Old Testament King...
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
LAYER DEEP-LEARNING
n.
Lager beer.
a.
Rising to the knees; knee-high; as, water or snow knee-deep.
a.
Sunk to the knees; as, men knee-deep in water.
superl.
Profound; thorough; complete; unmixed; intense; heavy; heartfelt; as, deep distress; deep melancholy; deep horror.
n.
A lawyer.
n.
The deep sensitive and vascular layer of the skin and mucous membranes.
superl.
Hard to penetrate or comprehend; profound; -- opposed to shallow or superficial; intricate; mysterious; not obvious; obscure; as, a deep subject or plot.
superl.
Extending far back from the front or outer part; of great horizontal dimension (measured backward from the front or nearer part, mouth, etc.); as, a deep cave or recess or wound; a gallery ten seats deep; a company of soldiers six files deep.
a.
Laid deeply; formed with cunning and sagacity; as, deep-laid plans.
n.
The deep layer of mucous membranes beneath the epithelium.
n.
That which is deep, especially deep water, as the sea or ocean; an abyss; a great depth.
a.
Of or pertaining to the deeper parts of the sea; as, a deep-sea line (i. e., a line to take soundings at a great depth); deep-sea lead; deep-sea soundings, explorations, etc.
superl.
Low in situation; lying far below the general surface; as, a deep valley.
a.
Deep as from the breast to the feet; as high as the breast.
v. i.
To remain in any position or state; to continue; to abide; to stay; as, to keep at a distance; to keep aloft; to keep near; to keep in the house; to keep before or behind; to keep in favor; to keep out of company, or out reach.
n.
That which is laid; a stratum; a bed; one thickness, course, or fold laid over another; as, a layer of clay or of sand in the earth; a layer of bricks, or of plaster; the layers of an onion.
superl.
Strongly colored; dark; intense; not light or thin; as, deep blue or crimson.
superl.
Extending far below the surface; of great perpendicular dimension (measured from the surface downward, and distinguished from high, which is measured upward); far to the bottom; having a certain depth; as, a deep sea.
n.
The fronds of certain marine algae used as food, and for making a sauce called laver sauce. Green laver is the Ulva latissima; purple laver, Porphyra laciniata and P. vulgaris. It is prepared by stewing, either alone or with other vegetables, and with various condiments; -- called also sloke, or sloakan.