機(jī)器學(xué)習(xí)與人工智能領(lǐng)域中常用的英語詞匯

·MachineLearning(ML)-機(jī)器學(xué)習(xí)4)ConvolutionalNeuralNetwork(CNN)-卷積神9)GenerativeAdversarialNetwork(GAN)-生成對抗網(wǎng)絡(luò)4)ConvolutionalNeuralNet9)DecisionTreeAlgori2)MachineLearningMod2)TrainingDataset-訓(xùn)練數(shù)據(jù)集12)TrainingBatch-訓(xùn)練·SupervisedLearning-有監(jiān)督學(xué)習(xí)·UnsupervisedLearning-無監(jiān)督學(xué)習(xí)·ReinforcementLearning-強(qiáng)化學(xué)習(xí)·Semi-SupervisedLearning-半監(jiān)督學(xué)習(xí)20)OrdinalFeature-有序特征2.NeuralNetworksandDeepLearning(神經(jīng)網(wǎng)絡(luò)與深度學(xué)習(xí))·ConvolutionalNeuralNetwork(CNN)-卷積神經(jīng)網(wǎng)絡(luò)·RecurrentNeuralNetwork(RNN)-循環(huán)神經(jīng)網(wǎng)絡(luò)·LongShort-TermMemory(LSTM)-長短期記憶網(wǎng)絡(luò)16)NamedEntity·AttentionMechanism-注意力機(jī)制9)Dot-ProductAttenti·GenerativeAdversarialNetwork(GAN)-生成對抗網(wǎng)絡(luò)3)Discriminator·Encoder-Decoder-編碼器-解碼器4)Sequence-to-Sequence5)DomainAdaptation-領(lǐng)域自適應(yīng)20)AdversarialTransferLearning-對抗遷移·Pre-trainedModels-預(yù)訓(xùn)練模型8)LanguageModel-9)WassersteinDistance-Wasserstein距離·ActivationFunction-激活函數(shù)5)ParametricReLU(PReLU)-參數(shù)化ReLU6)ExponentialLinearUnit(ELU)-指數(shù)線性單元9)SoftmaxFunction-SoftMax函數(shù)14)CELU(ContinuousExponentialLinearUnit)-CELU(連續(xù)指數(shù)線性3)LearningRateD6)Momentum-動量4)StochasticGr·Epoch-訓(xùn)練周期3.MachineLearningTechniquesandAlgorithms(機(jī)器學(xué)習(xí)技術(shù)與算法)·DecisionTree-決策樹·K-NearestNeighbors(KNN)-K-最近鄰·NaiveBayes-樸素貝葉斯2)Centroid-質(zhì)心9)DBSCAN(Density-BasedSpatialClusteringofApplicationswithNoise)-基于密度的·PrincipalComponentAnalysis(PCA)-主成分分析·AnomalyDetection-異常檢測4.ApplicationsofAIandML(人工智能與機(jī)器學(xué)習(xí)的應(yīng)用)·NaturalLanguageProcessing(NLP)-自然語言處理·ComputerVision-計(jì)算機(jī)視覺·AutonomousVehicles-自動駕駛汽車·TimeSeriesAnalysis-時(shí)間序列分析2)ExplainableArtificial