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(ML (Gradient Descent, Feature Engineering, Support Vector Machine (SVM),…
ML
Gradient Descent
Learning Rate
Stochastic Gradient Descent
Batch Gradient Descent
Feature Engineering
Embedding Numerous Features
Kernel Models
Combining Predictive Features
Aggregation Models
Blending
Bagging
Boost
AdaBoost (Adaptive Boost)
Gradient Boost for Regression
Distilling Implicit Features
Extraction Models
Neural Network
Principal Component Analysis (PCA)
Support Vector Machine (SVM)
Hard-Margin Support Vector Machine (SVM)
Kernel Hard-Margin SVM
Soft-Margin SVM
Decision Tree
Random Forest
Confusion Matrix
Generative AI
Diffusion Model
Evidence Lower Bound (ELBO)
Variational Inference (VI)
Generative Adversarial Network (GAN)
Hidden Space
Flow-based Generative Model
Generative Adversarial Networks (GANs)
Vanishing Gradients
Wasserstein loss
Q-learning
off-policy Q-learning
Generative Adversarial Transformers
GANformer
Simplex attention
Duplex attention
Markov decision process (MDP)
SARSA
deep reinforcement learning (DRL)
deep neural networks (DNN)
Double Deep Q Network (DQN)
Proximal Policy Optimization (PPO)
temporal-difference (TD)
StyleGAN2
multi-layer bidirectional transformer encoder (BERT)
Frechet Inception Distance (FID)
Inception Score (IS)
Precision
Recall
UAE abnormal detection
auto-encoders
Image Gray Interpolation
Image Registration Algorithm
Principle of Nontext Matching
Stack self-coding network
DBN
Convolution Neural Network (CNN)
neural scene decoration
Generative AI
Latent diffusion model (LDM)
Generative adversarial network (GAN)
Diffusion model
Turing Machine
deterministic Turing machine (DTM)
non-deterministic Turing machine (NTM)
Lagrange Multiplier
Generative AI
Prompt Engineering
Few shot learning
Zero shot learning
Fine-tuning