Category:Terms
Pages in category "Terms"
The following 200 pages are in this category, out of 520 total.
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- A/B testing
- Accuracy
- Action
- Activation function
- Active learning
- AdaGrad
- Agent
- Agglomerative clustering
- AI Monarchy
- AI Parasite
- AI Project Management
- Anomaly detection
- Area under the PR curve
- Artificial general intelligence
- Attention
- Attribute
- Attribute sampling
- AUC (Area Under the Curve)
- AudioCraft
- Augmented reality
- Automation bias
- Average precision
- Axis-aligned condition
B
- Backdooring LLMs
- Backpropagation
- Bag of words
- Bagging
- Baseline
- Batch
- Batch normalization
- Batch size
- Bayesian neural network
- Bayesian optimization
- Bellman equation
- BERT (Bidirectional Encoder Representations from Transformers)
- Bias
- Bias (ethics/fairness)
- Bias (math) or bias term
- Bidirectional
- Bidirectional language model
- Bigram
- Binary classification
- Binary condition
- BLEU (Bilingual Evaluation Understudy)
- Boosting
- Bounding box
- Broadcasting
- Bucketing
- Burstiness
C
- Calibration layer
- Candidate generation
- Candidate sampling
- Categorical data
- Causal language model
- Centroid
- Centroid-based clustering
- Checkpoint
- Class
- Class-imbalanced dataset
- Classification model
- Classification threshold
- Clipping
- Cloud TPU
- Clustering
- Co-adaptation
- Co-training
- Collaborative filtering
- Condition
- Confirmation bias
- Confusion matrix
- Continuous feature
- Convenience sampling
- Convergence
- Convex function
- Convex optimization
- Convex set
- Convolution
- Convolutional filter
- Convolutional layer
- Convolutional neural network
- Convolutional operation
- Cost
- Counterfactual fairness
- Coverage bias
- Crash blossom
- Critic
- Cross-entropy
- Cross-validation
- Cursor Rules
D
- Dark Factory
- Data analysis
- Data augmentation
- Data parallelism
- DataFrame
- Dataset API (tf.data)
- Datasets
- Decision boundary
- Decision forest
- Decision threshold
- Decision tree
- Decoder
- Deep model
- Deep neural network
- Deep Q-Network (DQN)
- Demographic parity
- Denoising
- Dense feature
- Dense layer
- Depth
- Depthwise separable convolutional neural network (sepCNN)
- Derived label
- Device
- Dimension reduction
- Dimensions
- Discrete feature
- Discriminative model
- Discriminator
- Disparate impact
- Disparate treatment
- Divisive clustering
- Downsampling
- DQN
- Dropout regularization
- Dynamic
- Dynamic model
E
- Eager execution
- Early stopping
- Earth mover's distance (EMD)
- Embedding layer
- Embedding space
- Embedding vector
- Empirical risk minimization (ERM)
- Encoder
- Ensemble
- Entropy
- Environment
- Episode
- Epoch
- Epsilon greedy policy
- Equality of opportunity
- Equalized odds
- Estimator
- Example
- Experience replay
- Experimenter's bias
- Exploding gradient problem
F
- Fairness constraint
- Fairness metric
- False negative (FN)
- False negative rate
- False positive (FP)
- False positive rate (FPR)
- Feature
- Feature cross
- Feature engineering
- Feature extraction
- Feature importances
- Feature set
- Feature spec
- Feature vector
- Federated learning
- Feedback loop
- Feedforward neural network (FFN)
- Few-shot learning
- Fine tuning
- Forget gate
- Full softmax
- Fully connected layer
G
- GAN
- Generalization
- Generalization curve
- Generalized linear model
- Generative adversarial network (GAN)
- Generative model
- Generator
- Gini impurity
- GPT
- GPT (Generative Pre-trained Transformer)
- GPT-1
- GPT-2
- Gradient
- Gradient boosted (decision) trees (GBT)
- Gradient boosting
- Gradient clipping
- Gradient descent
- Graph
- Graph execution
- Greedy policy
- Grok 3 Jailbreak
- Ground truth
- Group attribution bias