Twitter-color Created with Sketch. Amazon-color Created with Sketch. Facebook-color Created with Sketch. github [#142] Created with Sketch. meta_fill Pinterest-color Created with Sketch. ProductHunt-color Created with Sketch. Spotify-color Created with Sketch. Threads Logo Streamline Icon: https://streamlinehq.com Yelp-color Created with Sketch. Youtube-color Created with Sketch.
TopAIToolsTopAITools
  • Công Cụ Miễn Phí
  • Danh Mục
  • Bảng xếp hạng
  • Ưu đãi
  • Gửi Công Cụ
VI
TopAIToolsTopAITools
TopAI

TopAITools

TopAITools, Các Công Cụ AI Hàng Đầu Tốt Nhất

AI Thuật ngữ|English简体中文繁體中文한국어日本語PortuguêsEspañolDeutschFrançaisTiếng Việt|Bản đồ

© 2026 TopAITools. Đã đăng ký bản quyền.

Về chúng tôi

  • Chính Sách Bảo Mật
  • Điều Khoản Dịch Vụ

Liên hệ

business@topaitoolsreview.com
Trang chủAI Thuật ngữDeep LearningBackpropagation là gì?

AI Thuật ngữ

0-9
1-shot learning3D Reconstruction5G + AI6DoF pose estimation7D representation8-bit quantization2-stage detector4D data0-shot learning9-layer network3D convolution
A
A/B TestingAccountabilityAccuracyAcoustic ModelingActivation FunctionsActive LearningActor-Critic MethodsActuatorsAdaDeltaAdaGradAdam OptimizerAdjusted R-SquaredAdversarial AttacksAffordance LearningAgent-Based ModelingAgentic AI / Autonomous AgentsAgentic AI FrameworksAgglomerative ClusteringAGI / Artificial General IntelligenceAI AcceleratorsAI Act (EU)AI AgentsAI AlignmentAI and BiasAI and SustainabilityAI APIsAI Art GenerationAI AssistantsAI AuditAI AuditingAI Bill of Rights (US Blueprint)AI ContainmentAI DemocratizationAI Ethics BoardsAI Ethics GuidelinesAI Feature StoreAI for Climate ChangeAI Generated ContentAI Governance FrameworksAI GuardrailsAI HallucinationsAI in Healthcare EthicsAI in WarfareAI LegislationAI LiteracyAI MarketplacesAI Model GovernanceAI Model HubAI Model RegistryAI Model WeightsAI Music GenerationAI OrchestrationAI PolicyAI RegulationsAI SafetyAI SecurityAI SingularityAI Transparency ReportAI WatermarkingAI WinterAI Workflow AutomationAI-as-a-ServiceAlan TuringAlgorithmic AccountabilityAlgorithmic Bias MitigationAlgorithmic DiscriminationAlgorithmic TransparencyAndrew NgAnomaly DetectionAnomaly Detection in SecurityAnthropicApache KafkaAPI DevelopmentAPI EndpointsApriori AlgorithmArtificial General Intelligence (AGI)Artificial Neural NetworksArtificial SuperintelligenceASICsAssociation Rule LearningAsynchronous Advantage Actor-CriticAttention MechanismsAUCAudio ClassificationAudio Signal ProcessingAugmented RealityAuthenticationAuthorizationAutoencoderAutoencodersAutomated ReasoningAutomatic Speech Recognition (ASR)AutomationAutoMLAutonomous NavigationAutoregressive ModelsAttentionAlgorithmArtificial Intelligence (AI)
B
BackpropagationBag-of-Words ModelBaggingBatch SizeBayesian InferenceBayesian NetworksBayesian OptimizationBERTBias in AIBias-Variance TradeoffBig DataBig Data TechnologiesBiometric SecurityBLEU ScoreBlockchain in AIBoostingBox PlotByte-Pair Encoding (BPE)Batch NormalizationBias
C
CaffeCalculusCalibrationCalifornia Consumer Privacy Act (CCPA)Canary DeploymentCapsule NetworksCarbon Footprint of AICase-Based ReasoningCatastrophic ForgettingCentral Limit TheoremChain-of-ThoughtChatbotChinese Room ArgumentClass ImbalanceClassificationCloud AI PlatformsCloud ComputingClustering AlgorithmsClusteringCNN / Convolutional Neural NetworkCode Generation ModelsCognitive ArchitecturesCognitive ComputingCohereColab NotebooksCollaborative FilteringColor SpacesComplex AnalysisComplianceCompliance Standards (ISO IEEE)Computational ComplexityComputational Fluid DynamicsComputational Theory of MindCompute-Optimal ModelsConcept DriftConceptual GraphsConditional ProbabilityConfusion MatrixConsciousness in AIConsistency ModelsConstitutional AIConstraint Satisfaction ProblemsContainerizationContent-Based FilteringContext WindowContinual LearningContinuous Integration/Continuous Deployment (CI/CD)Control SystemsConversational AIConvolutional Neural NetworksCOPPACoreference ResolutionCorrelationCorrelation MatrixCost-Sensitive LearningCross-Entropy LossCross-ValidationCurriculum LearningCyber Threat IntelligenceCybersecurity RegulationsClassifier / Classification
D
DALL·EData AnnotationData CatalogData CentersData CleaningData DriftData GovernanceData IngestionData IntegrationData LabelingData LakeData LakesData LeakageData LineageData MiningData PipelineData PoisoningData PreprocessingData PrivacyData ProtectionData Protection LawsData QualityData SecurityData SovereigntyData TransformationData VersioningData VisualizationData Visualization TechniquesData WarehousingDatabases for AIDavies-Bouldin IndexDBSCANDecision Boundary VisualizationDecision TreesDeep Belief NetworksDeep LearningDeep Q-NetworksDeep Reinforcement LearningDeepfakeDeepfakesDeepMindDemis HassabisDependency ParsingDepth EstimationDescriptive StatisticsDialogue SystemsDifferential EquationsDifferential EvolutionDifferential PrivacyDiffusion ModelsDigital DivideDigital ProvenanceDigital TwinsDimensionality ReductionDirect Preference Optimization (DPO)Discourse AnalysisDiscrete Event SimulationDiscrete MathematicsDisinformationDistributed ComputingDistributed File SystemsDistributed TrainingDockerDronesDropoutDropout RegularizationDynamical SystemsDiscriminative ModelDeterministic ModelData Augmentation
E
Early StoppingEdge AIEdge ComputingEdge DetectionEigenvalues and EigenvectorsElon MuskEmbeddingEmbedding SizeEmbeddingsEmbodied AIEmergent AbilitiesEmotion RecognitionEncoderEnsemble MethodsEpisodic MemoryEpochEthical AIEthical AI GuidelinesEthical AuditingEthical Decision-MakingEthical DilemmasEthical FrameworksEthics of AIETL ProcessesEvolutionary AlgorithmsExistential RiskExpectation-MaximizationExpectation-Maximization AlgorithmExpected Calibration ErrorExpert SystemsExplainabilityExploration vs. ExploitationExploratory Data AnalysisExport ControlsEnsemble LearningExplainable AI (XAI)
F
F1 ScoreFacial RecognitionFairnessFastAIFeature EngineeringFeature ImportanceFeature SelectionFeature StoreFeature StoresFederated LearningFei-Fei LiFew-Shot LearningFine-tuningFinite Element AnalysisFirst-Order LogicFlow MatchingForce ControlFoundation Model EconomyFoundation ModelsFourier TransformFPGAsFrame LanguagesFunctional AnalysisFusion / Multimodal FusionForward PropagationFoundation ModelFeature Extraction
G
Game Playing AIGame TheoryGame Theory SimulationsGAN / Generative Adversarial NetworkGated Recurrent UnitsGaussian Mixture ModelsGeneral Data Protection Regulation (GDPR)Generative Adversarial NetworksGenerative ModelsGenetic AlgorithmsGensimGeoffrey HintonGlobal CooperationGPT ModelsGrad-CAMGradient Boosting MachinesGradient ClippingGradient DescentGraph Neural NetworksGraph TheoryGraphics Processing Units (GPUs)Grid SearchGroundingGraph Neural Network (GNN)Generative AI
H
HadoopHeatmapHelpHeuristic AlgorithmsHidden Markov ModelsHierarchical Reinforcement LearningHigh-Performance ComputingHIPAAHyperparameterHistogramHOGHPC ClustersHugging FaceHugging Face TransformersHuman RightsHuman-in-the-LoopHuman-Robot InteractionHyperparameter OptimizationHyperparameter TuningHeuristicHidden LayerHierarchical ModelHallucination
I
Imbalanced DataInterpretabilityIlya SutskeverImage CaptioningImage ClassificationImage RecognitionImage SegmentationImpact on EmploymentIn-Context LearningIndustrial RobotsInferenceInference EnginesInference OptimizationInferential StatisticsInformation TheoryInformed ConsentInfrastructure as CodeInstance SegmentationInstruction tuningIntellectual Property RightsIntelligent AgentsIntrusion Detection SystemsInverse Reinforcement LearningInstance / SampleIntelligence Amplification / Augmentation
J
JAXJitteringJohn McCarthyJoint EmbeddingJoint Probability DistributionJSONL / JSON-linesJuergen SchmidhuberJupyter NotebooksJuxtaposition
K
KL Divergence (Kullback–Leibler Divergence)K-means ClusteringK-Nearest NeighborsK-Shot LearningKai-Fu LeeKalman FiltersKerasKernel TrickKnowledge DistillationKnowledge CutoffKnowledge GraphsKnowledge RepresentationKubernetes
L
Latent VariableLoss FunctionL1 RegularizationL2 RegularizationLabel SmoothingLanguage ModelingLanguage ModelsLaplace TransformLarge Language Models (LLMs)Large Multimodal ModelsLatent Dirichlet AllocationLatent SpaceLaw of Large NumbersLayer NormalizationLearning CurveLearning Rate DecayLearning Rate SchedulingLemmatizationLIMELinear AlgebraLinear RegressionLog LossLogic ProgrammingLogistic RegressionLong Short-Term Memory NetworksLong-Context ModelsLoRA (Low-Rank Adaptation)LSTM / Long Short-Term MemoryLarge Language Model (LLM)Learning Rate
M
Multimodal / MultimodalityMachine Learning (ML)Machine ConsciousnessMachine TranslationMarkov Chain ModelsMarkov Chain Monte CarloMarkov Decision ProcessesMarkov ModelsMarvin MinskyMasked Language ModelsMaster Data ManagementMatplotlibMatrix DecompositionMCPMean Absolute ErrorMean Squared ErrorMechanistic InterpretabilityMel-Frequency Cepstral Coefficients (MFCCs)Meta-learningMetadata ManagementMicroservicesMidjourneyMind UploadingMini ToolMini-Batch Gradient DescentMixture of Experts (MoE)MLOpsMobile RobotsModel CardsModel CompressionModel DeploymentModel DriftModel Explainability ToolsModel MonitoringModel ServingModel StealingMomentum OptimizationMonitoring and LoggingMonte Carlo MethodsMonte Carlo SimulationsMoral MachinesMotion DetectionMotion PlanningModelMulti-Armed Bandit ProblemMulti-head AttentionMultimodal AIMusic Information RetrievalMXNet
N
NormalizationNeural Networkn-GramsNaive Bayes AlgorithmNaive Bayes ClassifierNamed Entity RecognitionNatural Language Generation (NLG)Natural Language ProcessingNatural Language Processing (NLP)Natural Language UnderstandingNesterov Accelerated GradientNetwork SimulationsNeural Architecture SearchNeural NetworksNeural Processing Unit (NPU)Neuromorphic ComputingNick BostromNLP / Natural Language ProcessingNLTKNLU / Natural Language UnderstandingNoise ReductionNoSQL DatabasesNumPyNVIDIA CUDANovelty Detection / Anomaly Detection
O
Objective FunctionOnline LearningObject DetectionObject TrackingOne-hot EncodingOntologiesOpenAIOpenAI GPTOptical Character RecognitionOptimization TheoryOut-of-Distribution (OOD) DataOverfittingOptimizer
P
Policy / Reinforcement Learning PolicyPandasParallel ComputingParameter CountParameter-Efficient Fine-Tuning (PEFT)Part-of-Speech TaggingPartial Dependence PlotsPath PlanningPattern RecognitionPeople also viewedPerception in AIPerceptronPerplexityPeter NorvigPhilosophy of MindPhoneticsPipelinesPlanning and SchedulingPlotlyPolicy GradientsPolicy OptimizationPoolingPose EstimationPositional EncodingPragmaticsPrecisionPredictive ModelingPredictive ProbabilityPreference TuningPretrainingPrincipal Component AnalysisPrivacyPrivacy-Preserving Machine LearningProbability Density FunctionsProbability TheoryProblem SolvingProcess ModelingProcess-Based SupervisionPrompt ChainingPrompt EngineeringPrompt InjectionPromptPrompt MarketplacePrompt TemplatesPropositional LogicProximal Policy OptimizationPruningPyTorchParameter
Q
Queue / BufferQuantizationQ-learningQLoRA (Quantized Low-Rank Adaptation)Quantum ComputingQuantum Machine LearningQuestion AnsweringQuestion Answering SystemsQueryQuality Estimation
R
Retrieval Augmented Generation (RAG)Representation LearningReinforcement Learning (RL)R-SquaredRandom ForestsRandom SearchRay KurzweilReal AnalysisReasoning EnginesRecallRecommender SystemsRecurrent Neural NetworksRed TeamingRegressionRegression AnalysisRegularizationRegulatory ComplianceReinforcement Learning from Human FeedbackReinforcement Learning in RoboticsReproducibilityResponsible AIRetrieval-Augmented GenerationReward FunctionRMSpropRNN / Recurrent Neural NetworkRobot KinematicsRobot VisionRobotic ManipulationRobotic Operating System (ROS)Robotics TransformersRobustness in AI ModelsROC CurveRodney BrooksRoot Mean Squared ErrorRule-Based Systems
S
Supervised LearningSelf-Supervised LearningSequence ModelingSaliency MapsSamplingSARSA AlgorithmScalable OversightScaling LawsScatter PlotScikit-LearnSciPySeabornSearch AlgorithmsSecure HardwareSecure Multi-Party ComputationSecure ProtocolsSelf-AttentionSelf-Driving CarsSemantic NetworksSemantic ParsingSemantic Role LabelingSemantic SegmentationSemantic WebSemi-Supervised LearningSensorsSentencePieceSentiment AnalysisSequence LabelingServerless ComputingServerless GPUsSet TheorySHAP ValuesSiamese NetworksSIFTSilhouette ScoreSimulated AnnealingSimulation HypothesisSimulation-to-Real Transfer (Sim2Real)Simultaneous Localization and Mapping (SLAM)SMOTESocial Acceptance of AISocial SimulationSoftmaxSOTA (State of the Art)spaCySparkSpeaker DiarizationSpectrogram AnalysisSpeech EnhancementSpeech RecognitionSpeech SynthesisSpiking Neural NetworksSQLStable DiffusionStackingState-Action PairsStatistical AnalysisStatistical DistributionsStatisticsStemmingStochastic Gradient DescentStochastic ModelingStochastic ProcessesStop WordsStream ProcessingStrong AIStrong vs. Weak AIStuart RussellStyle TransferSubword TokenizationSupport Vector MachinesSURFSurveillanceSwarm IntelligenceSymbolic AISynthetic Data GenerationSynthetic MediaSystem DynamicsSystem Prompt
T
Training Datat-SNETeacher ForcingTechnological SingularityTeleoperationTemperatureTemporal Difference LearningTensor Processing Units (TPUs)TensorFlowTesting and ValidationText SummarizationText-to-Audio GenerationText-to-Image GenerationText-to-Speech (TTS)Text-to-Video GenerationTF-IDFTheanoTime Series AnalysisTimnit GebruTinyMLToken LimitTokenizationTokenizerTokensTool Use (LLMs)Topic ModelingTopologyTransfer LearningTransformerTransformer ModelsTransformer NetworksTransparencyTransparency RequirementsTrust Region Policy OptimizationTrustworthy AITruthfulness (in LLMs)Tuning / Hyperparameter TuningTuring Test
U
Universal Approximation TheoremUnsupervised LearningU-NetUMAPUnderfittingUnmanned Aerial Vehicles (UAVs)Unmanned Ground VehiclesUncertainty Estimation
V
Variational Autoencoder (VAE)Vector EmbeddingVanishing / Exploding GradientValidation SetValidation CurveValue FunctionVector DatabaseVersion Control for ModelsVibe code an AI ToolVideo Generation ModelsVirtual Reality SimulationsVision Transformer (ViT)Voice BiometricsVoice CloningVoice Conversion
W
Weak SupervisionWarmup StepsWeak AIWeight DecayWhitening / Whitening TransformationWord EmbeddingWord EmbeddingsWord Sense DisambiguationWordPieceWorkflowWorld Models
X
XOR problemX-axis / feature axisXAI / Explainable AIXLMXLNet
Y
Y-axis / feature axisY-transform / YUVYAGNI (You Aren't Gonna Need It)Yann LeCunYield (model yield / throughput)Yoga of AIYoshua Bengio
Z
Z-score NormalizationZero-gradient phenomenonZero-shot Learning / Zero-shot inferenceZero-centric / Zero-bias initializationZero Trust ArchitectureZygosity in augmentation

Backpropagation là gì?

Deep Learning
[wˌʌt ɪz bˌækpɹəpɐɡˈeɪʃən]
Cập nhật lần cuối: 15 tháng 10, 2025

Backpropagation là một thuật toán được sử dụng để huấn luyện mạng nơ-ron nhân tạo, tính toán các gradient của hàm mất mát liên quan đến trọng số của mạng để giảm thiểu lỗi.


Phương pháp này là cơ sở của học sâu và được áp dụng rộng rãi trong nhiều nhiệm vụ học máy, bao gồm nhận dạng hình ảnh và xử lý ngôn ngữ tự nhiên.


Nguyên tắc cơ bản của backpropagation bao gồm hai giai đoạn chính: lan truyền tiến, tính toán đầu ra; và lan truyền ngược, tính toán gradient và cập nhật trọng số.


Mặc dù backpropagation có nhiều ưu điểm như hiệu quả và khả năng thích ứng với các tập dữ liệu lớn, nhưng cũng có những nhược điểm như nhạy cảm với trọng số ban đầu và các vấn đề về gradient biến mất hoặc bùng nổ.


Các xu hướng trong tương lai có thể thấy backpropagation được kết hợp với các thuật toán tiên tiến khác để cải thiện cơ chế huấn luyện và vượt qua những hạn chế của nó.

Thuật ngữ liên quan

Autoencoder là gì

Khám phá Autoencoder: thuật toán học không giám sát cho nén dữ liệu và trích xuất đặc trưng không có...

Deep Learning

Chuẩn hóa theo lô là gì

Chuẩn hóa theo lô là kỹ thuật chủ chốt trong học sâu, cải thiện tốc độ và độ ổn định của quá trình đ...

Deep Learning

Deep Learning là gì

Tìm hiểu về deep learning, tầm quan trọng của nó trong AI, ứng dụng trong nhiều lĩnh vực và những ưu...

Deep Learning

Encoder là gì

Tìm hiểu về Encoder, thiết bị chuyển đổi định dạng dữ liệu cho việc lưu trữ và truyền tải hiệu quả. ...

Deep Learning