The following algorithms are covered in this book: •    ADABOOST •    ADAM OPTIMIZATION •    AGGLOMERATIVE CLUSTERING •    ARMA/ARIMA MODEL •    BERT •    CONVOLUTIONAL NEURAL NETWORK •    DBSCAN •    DECISION TREE •    DEEP Q-LEARNING •    EFFICIENTNET •    FACTOR ANALYSIS OF CORRESPONDENCES •    GAN •    GMM •    GPT-3 •    GRADIENT BOOSTING MACHINE •    GRADIENT DESCENT •    GRAPH NEURAL NETWORKS •    HIERARCHICAL CLUSTERING •    HIDDEN MARKOV MODEL (HMM) •    INDEPENDENT COMPONENT ANALYSIS •    ISOLATION FOREST •    K-MEANS •    K-NEAREST NEIGHBOUR •    LINEAR REGRESSION •    LOGISTIC REGRESSION •    LSTM •    MEAN SHIFT •    MOBILENET •    MONTE CARLO ALGORITHM •    MULTIMODAL PARALLEL NETWORK •    NAIVE BAYES CLASSIFIERS •    PROXIMAL POLICY OPTIMIZATION •    PRINCIPAL COMPONENT ANALYSIS •    Q-LEARNING •    RANDOM FORESTS •    RECURRENT NEURAL NETWORK •    RESNET •    SPATIAL TEMPORAL GRAPH CONVOLUTIONAL NETWORKS •    STOCHASTIC GRADIENT DESCENT •    SUPPORT VECTOR MACHINE •    WAVENET •    XGBOOST