Category:Machine learning
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scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions  A kernel machine is a set of algorithms used in machine learning to compute non-linearly separable functions into a higher dimension linearly separable function  | |||||
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English: 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 40 subcategories, out of 40 total.
*
A
C
- Case-based reasoning (5 F)
D
- Data spirals (6 F)
E
- Tina Eliassi-Rad (4 F)
G
H
I
K
M
- Markov models (31 F)
O
- ORES (2 F)
- Overfitting (13 F)
P
R
- Reinforcement learning (21 F)
S
- Stockfish (chess) (4 F)
- Support vector machine (24 F)
T
- Thought cloning in AI (8 F)
U
- Underfitting (2 F)
V
- Vowpal Wabbit (2 F)
Pages in category "Machine learning"
This category contains only the following page.
Media in category "Machine learning"
The following 200 files are in this category, out of 456 total.
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De-maschinelles Lernen.ogg 2.1 s; 20 KB
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1D Convolution.png 321 × 310; 11 KB
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1D Convolutional Neural Network feed forward example.png 661 × 301; 31 KB
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A hybrid deep learning approach for medical relation extraction.pdf 1,275 × 1,650, 4 pages; 570 KB
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AI End-Scenario Six Avenues for AI takeover tamingtheaibeast.png 3,285 × 2,131; 547 KB
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AI Techniques Overview.png 860 × 624; 71 KB
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AI Types. Tipos Inteligencia Artificial.svg 953 × 899; 22 KB
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Amortized hardware and energy cost to train frontier AI models over time.png 2,400 × 1,572; 242 KB
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Architecture d'un Transformeur.png 1,600 × 1,440; 380 KB
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Artificial grammar learning example.jpg 462 × 252; 28 KB
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Artificial Neural Network with Chip.jpg 2,000 × 1,600; 2.59 MB
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ATW CNN architecture.png 3,360 × 5,019; 807 KB
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Augmentation Content Curation DRAFT.pdf 1,275 × 1,650, 7 pages; 261 KB
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Augmentation Content Generation DRAFT.pdf 1,275 × 1,650, 6 pages; 260 KB
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Augmentation Governance DRAFT.pdf 1,275 × 1,650, 5 pages; 284 KB
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Augmentation Machine Translation DRAFT.pdf 1,275 × 1,650, 8 pages; 1.25 MB
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Augmentor.png 330 × 182; 25 KB
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Bayessches Netz.png 607 × 250; 4 KB
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Beta Trial PhyzBatch-9000.png 4,032 × 3,024; 8.86 MB
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Beyond Human Journey Towards A.I World Book By Deepak Dinesh Kapadnis.jpg 1,242 × 1,755; 317 KB
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Big Bench Hard performance vs AI scale.png 2,400 × 1,500; 154 KB
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BPM input space wiki.pdf 1,239 × 1,752; 381 KB
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BPM MLP wiki.pdf 1,239 × 1,752; 383 KB
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C.EstelleSmith ResearchShowcase 5 20 20.pdf 1,500 × 1,125, 50 pages; 2.23 MB
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Calibration plot.png 1,000 × 1,000; 109 KB
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Carto IA deepLearning.svg 1,034 × 871; 11 KB
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CB pdf.png 858 × 683; 101 KB
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Climate data analysis using tSNE method.png 814 × 805; 94 KB
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CollieBrownArghonCEO.jpg 965 × 1,241; 307 KB
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Compactness Comparison of Linear and Multilinear Projections.png 791 × 614; 65 KB
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Confusion matrix.png 1,557 × 805; 82 KB
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Convolutional-neural-network-polyanalyst-flowchart-example.png 561 × 190; 20 KB
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ConvolutionAndPooling.svg 839 × 208; 160 KB
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CorteX Carte Predpol.jpg 446 × 196; 93 KB
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CRAIYON-REALESRGAN-Dalmatian bench.jpg 1,024 × 1,024; 293 KB
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Data Augmentation of rock images revised.jpg 1,280 × 1,440; 472 KB
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David Weinberger with blue checks - 2019.png 2,793 × 2,845; 11.34 MB
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Dean Weber.png 957 × 931; 1.76 MB
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Decaying Sine Unit (DSU).png 3,000 × 2,000; 420 KB
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Deep learning fait parti de l'IA.png 621 × 598; 37 KB
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DeepInsight method to transform non-image data to 2D image for convolutional neural network architecture.pdf 1,239 × 1,629, 7 pages; 1.78 MB
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DeepLearningReconstruction.png 2,502 × 600; 617 KB
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DeepMoji examples histogram.png 850 × 1,224; 139 KB
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DenseCap (Johnson et al., 2016) (cropped).png 702 × 495; 489 KB
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EfficientNetB3V2.jpg 720 × 720; 66 KB
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Employee Attrition Prediction.pdf 1,275 × 1,650, 3 pages; 619 KB
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EncoderDecoder.pdf 1,275 × 458; 9 KB
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EVA Lernen Training.svg 1,052 × 744; 41 KB
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Example for Adjusted Rand index.svg 900 × 360; 467 KB
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Feature Learning Diagram.png 1,000 × 333; 32 KB
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Feature selection Embedded Method.png 1,279 × 379; 46 KB
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Federated learning (centralized vs decentralized).png 2,504 × 1,266; 232 KB
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Federated learning (horizontal vs. vertical.png 1,866 × 1,404; 233 KB
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Filter Methode.png 932 × 92; 30 KB
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Flores de Íris.png 1,945 × 977; 1.99 MB
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Flowchart of the spatio-temporal action localization detector Segment-tube.png 3,934 × 3,280; 1.93 MB
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FreqGenSchema.png 1,408 × 829; 28 KB
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Frequency distribution of pre-processing techniques.jpg 864 × 428; 37 KB
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Frequency experiment two dimension.png 1,087 × 270; 181 KB
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FullSLAM.png 600 × 396; 15 KB
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Gaussian process draws from prior distribution.png 1,200 × 400; 112 KB
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Gaussian Process Regression.png 1,200 × 400; 98 KB
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GaussianScatterPCA.svg 720 × 720; 515 KB
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GMilovanovic eRum2018.pdf 1,654 × 1,239, 14 pages; 1.02 MB
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Gradient descent with momentum.svg 512 × 549; 316 KB
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Gradio example.png 1,119 × 930; 671 KB
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Growing Cosine Unit (GCU) activation function.png 3,000 × 2,186; 273 KB
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Hinge loss variants.svg 720 × 540; 21 KB
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Idistance.jpg 601 × 351; 26 KB
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Illustration of imperceptible adversarial pertubation.png 680 × 262; 190 KB
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Image Content filtration - Outreachy.pdf 2,000 × 1,125, 32 pages; 931 KB
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Info Gain Root Split Example.png 281 × 351; 15 KB
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Info Gain Splitting the Child Node(s) Example.png 361 × 511; 23 KB
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Instance-based learning.jpg 796 × 533; 81 KB
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Integrated-stacking.png 8,192 × 3,807; 1.11 MB
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Intersection over Union - object detection bounding boxes.jpg 600 × 450; 92 KB
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Intersection over Union - poor, good and excellent score.png 600 × 248; 8 KB
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Iris Flowers Clustering kMeans de.svg 660 × 309; 145 KB
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Iris Flowers Clustering kMeans.svg 660 × 309; 145 KB
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K-fold cross validation EN.svg 555 × 275; 230 KB
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Knowledge Graph Embedding.pdf 1,293 × 585; 182 KB
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L1-PCA.png 1,750 × 1,313; 82 KB
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Language model in Deepmind's 2021 Retro for RAG.svg 512 × 314; 51 KB
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Lasso Regression.png 521 × 442; 22 KB
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