Pages that link to "Machine learning terms"
The following pages link to Machine learning terms:
Displayed 500 items.
- Neural network (← links)
- Artificial Intelligence (← links)
- Terms (transclusion) (← links)
- To-Do List (← links)
- ML terms (redirect page) (← links)
- Accuracy (← links)
- Machine learning (← links)
- Backpropagation (← links)
- Batch size (← links)
- Batch (← links)
- Bias (ethics/fairness) (← links)
- Bias (← links)
- Binary classification (← links)
- Activation function (← links)
- AUC (Area Under the Curve) (← links)
- Bucketing (← links)
- Categorical data (← links)
- Class (← links)
- Embedding layer (← links)
- Epoch (← links)
- Example (← links)
- False negative (FN) (← links)
- False positive (FP) (← links)
- False positive rate (FPR) (← links)
- Feature cross (← links)
- Feature (← links)
- Classification model (← links)
- Classification threshold (← links)
- Continuous feature (← links)
- Feature engineering (← links)
- Feature set (← links)
- Class-imbalanced dataset (← links)
- Clipping (← links)
- Convergence (← links)
- DataFrame (← links)
- Datasets (← links)
- Deep model (← links)
- Dense feature (← links)
- Depth (← links)
- Discrete feature (← links)
- Dynamic (← links)
- Online learning (← links)
- Early stopping (← links)
- Dynamic model (← links)
- Training set (← links)
- True negative (TN) (← links)
- True positive (TP) (← links)
- True positive rate (TPR) (← links)
- Underfitting (← links)
- Unlabeled example (← links)
- Unsupervised machine learning (← links)
- Validation loss (← links)
- Validation set (← links)
- Validation (← links)
- Weight (← links)
- Weighted sum (← links)
- Z-score normalization (← links)
- Feature vector (← links)
- Feedback loop (← links)
- Generalization curve (← links)
- Generalization (← links)
- Gradient descent (← links)
- Ground truth (← links)
- Hidden layer (← links)
- Hyperparameter (← links)
- Inference (← links)
- Independently and identically distributed (i.i.d.) (← links)
- Input layer (← links)
- Interpretability (← links)
- Iteration (← links)
- Stability (← links)
- L0 regularization (← links)
- Training-serving skew (← links)
- Training loss (← links)
- Training (← links)
- Test loss (← links)
- Machine learning terms/All (← links)
- Machine learning terms/Fundamentals (← links)
- Machine learning terms/Fairness (← links)
- Machine learning terms/Recommendation Systems (← links)
- Machine learning terms/Computer Vision (← links)
- Machine learning terms/Clustering (← links)
- Machine learning terms/Natural Language Processing (← links)
- Machine learning terms/TensorFlow (← links)
- Machine learning terms/Decision Forests (← links)
- Machine learning terms/Sequence Models (← links)
- Machine learning terms/Reinforcement Learning (← links)
- Machine learning terms/Google Cloud (← links)
- ML Terms (redirect page) (← links)
- AI ML Wiki (← links)
- A/B testing (← links)
- Action (← links)
- Active learning (← links)
- AdaGrad (← links)
- Agent (← links)
- Agglomerative clustering (← links)
- Anomaly detection (← links)
- AR (← links)
- Area under the PR curve (← links)
- Artificial general intelligence (← links)
- Attention (← links)
- Attribute sampling (← links)
- Attribute (← links)
- Augmented reality (← links)
- Automation bias (← links)
- Learning rate (← links)
- Layer (← links)
- Mini-batch (← links)
- Majority class (← links)
- Minority class (← links)
- BERT (Bidirectional Encoder Representations from Transformers) (← links)
- BLEU (Bilingual Evaluation Understudy) (← links)
- GPT (Generative Pre-trained Transformer) (← links)
- L1 loss (← links)
- L1 regularization (← links)
- L2 loss (← links)
- L2 regularization (← links)
- LaMDA (Language Model for Dialogue Applications) (← links)
- Log Loss (← links)
- N-gram (← links)
- NLU (← links)
- ROC (receiver operating characteristic) Curve (← links)
- ReLU (← links)
- Rectified Linear Unit (ReLU) (← links)
- Root Mean Squared Error (RMSE) (← links)
- Bag of words (← links)
- Bidirectional (← links)
- Bidirectional language model (← links)
- Bigram (← links)
- Causal language model (← links)
- Confusion matrix (← links)
- Crash blossom (← links)
- Decoder (← links)
- Denoising (← links)
- Embedding space (← links)
- Embedding vector (← links)
- Encoder (← links)
- Label (← links)
- Labeled example (← links)
- Lambda (← links)
- Language model (← links)
- Large language model (← links)
- Linear (← links)
- Linear model (← links)
- Linear regression (← links)
- Log-odds (← links)
- Logistic regression (← links)
- Loss (← links)
- Loss curve (← links)
- Loss function (← links)
- Masked language model (← links)
- Meta-learning (← links)
- Modality (← links)
- Model (← links)
- Model parallelism (← links)
- Multi-class classification (← links)
- Multi-head self-attention (← links)
- Multimodal model (← links)
- Natural language understanding (← links)
- Negative class (← links)
- Neuron (← links)
- Node (neural network) (← links)
- Nonlinear (← links)
- Nonstationarity (← links)
- Normalization (← links)
- Numerical data (← links)
- Offline (← links)
- Offline inference (← links)
- One-hot encoding (← links)
- One-vs.-all (← links)
- Online inference (← links)
- Output layer (← links)
- Overfitting (← links)
- Pandas (← links)
- Parameter (← links)
- Pipelining (← links)
- Positive class (← links)
- Post-processing (← links)
- Prediction (← links)
- Proxy labels (← links)
- Rater (← links)
- Regression model (← links)
- Regularization (← links)
- Regularization rate (← links)
- Self-attention (also called self-attention layer) (← links)
- Sentiment analysis (← links)
- Sequence-to-sequence task (← links)
- Sigmoid function (← links)
- Softmax (← links)
- Sparse feature (← links)
- Sparse representation (← links)
- Sparse vector (← links)
- Squared loss (← links)
- Staged training (← links)
- Static (← links)
- Static inference (← links)
- Stationarity (← links)
- Stochastic gradient descent (SGD) (← links)
- Supervised machine learning (← links)
- Synthetic feature (← links)
- Transformer (← links)
- Axis-aligned condition (← links)
- Bagging (← links)
- Binary condition (← links)
- Condition (← links)
- Decision forest (← links)
- Decision tree (← links)
- Entropy (← links)
- Feature importances (← links)
- Gini impurity (← links)
- Gradient boosted (decision) trees (GBT) (← links)
- Gradient boosting (← links)
- In-set condition (← links)
- Inference path (← links)
- Information gain (← links)
- Leaf (← links)
- Node (decision tree) (← links)
- Non-binary condition (← links)
- Oblique condition (← links)
- Out-of-bag evaluation (OOB evaluation) (← links)
- Token (← links)
- Trigram (← links)
- Unidirectional (← links)
- Unidirectional language model (← links)
- Word embedding (← links)
- Bellman equation (← links)
- DQN (← links)
- Deep Q-Network (DQN) (← links)
- Markov decision process (MDP) (← links)
- Markov property (← links)
- Q-function (← links)
- Q-learning (← links)
- Critic (← links)
- Environment (← links)
- Episode (← links)
- Epsilon greedy policy (← links)
- Experience replay (← links)
- Greedy policy (← links)
- Permutation variable importances (← links)
- Policy (← links)
- Random forest (← links)
- Root (← links)
- Sampling with replacement (← links)
- Shrinkage (← links)
- Split (← links)
- Splitter (← links)
- Threshold (for decision trees) (← links)
- Variable importances (← links)
- Wisdom of the crowd (← links)
- MNIST (← links)
- Bounding box (← links)
- Convolution (← links)
- Convolutional filter (← links)
- Convolutional layer (← links)
- Convolutional neural network (← links)
- Convolutional operation (← links)
- Data augmentation (← links)
- Depthwise separable convolutional neural network (sepCNN) (← links)
- Downsampling (← links)
- Image recognition (← links)
- Intersection over union (IoU) (← links)
- Keypoints (← links)
- Landmarks (← links)
- Random policy (← links)
- Reinforcement learning (RL) (← links)
- Replay buffer (← links)
- Return (← links)
- Reward (← links)
- State-action value function (← links)
- State (← links)
- Tabular Q-learning (← links)
- Target network (← links)
- Termination condition (← links)
- Trajectory (← links)
- LSTM (← links)
- Long Short-Term Memory (LSTM) (← links)
- RNN (← links)
- Centroid-based clustering (← links)
- Centroid (← links)
- Clustering (← links)
- Divisive clustering (← links)
- Exploding gradient problem (← links)
- Forget gate (← links)
- Gradient clipping (← links)
- Hierarchical clustering (← links)
- Pooling (← links)
- Recurrent neural network (← links)
- Rotational invariance (← links)
- Sequence model (← links)
- Size invariance (← links)
- Spatial pooling (← links)
- Stride (← links)
- Subsampling (← links)
- Timestep (← links)
- Translational invariance (← links)
- Vanishing gradient problem (← links)
- Bayesian neural network (← links)
- Bayesian optimization (← links)
- Cloud TPU (← links)
- Average precision (← links)
- Baseline (← links)
- Batch normalization (← links)
- Bias (math) or bias term (← links)
- Boosting (← links)
- Broadcasting (← links)
- Calibration layer (← links)
- Candidate generation (← links)
- Candidate sampling (← links)
- Checkpoint (← links)
- Co-adaptation (← links)
- Collaborative filtering (← links)
- Confirmation bias (← links)
- Convenience sampling (← links)
- Convex function (← links)
- Convex optimization (← links)
- K-means (← links)
- K-median (← links)
- Similarity measure (← links)
- Sketching (← links)
- Time series analysis (← links)
- Dataset API (tf.data) (← links)
- Co-training (← links)
- Convex set (← links)
- Cost (← links)
- Counterfactual fairness (← links)
- Coverage bias (← links)
- Cross-entropy (← links)
- Cross-validation (← links)
- Data analysis (← links)
- Data parallelism (← links)
- Decision boundary (← links)
- Decision threshold (← links)
- Deep neural network (← links)
- Demographic parity (← links)
- Dense layer (← links)
- Derived label (← links)
- Device (← links)
- Dimension reduction (← links)
- Dimensions (← links)
- Discriminative model (← links)
- Discriminator (← links)
- Disparate impact (← links)
- Disparate treatment (← links)
- Dropout regularization (← links)
- Eager execution (← links)
- Estimator (← links)
- GAN (← links)
- Earth mover's distance (EMD) (← links)
- Empirical risk minimization (ERM) (← links)
- Ensemble (← links)
- Equality of opportunity (← links)
- Equalized odds (← links)
- Experimenter's bias (← links)
- Fairness constraint (← links)
- Fairness metric (← links)
- False negative rate (← links)
- Feature extraction (← links)
- Feature spec (← links)
- Federated learning (← links)
- Feedforward neural network (FFN) (← links)
- Few-shot learning (← links)
- Fine tuning (← links)
- Full softmax (← links)
- Fully connected layer (← links)
- Generalized linear model (← links)
- Generative adversarial network (GAN) (← links)
- Generative model (← links)
- Generator (← links)
- Gradient (← links)
- IoU (← links)
- Keras (← links)
- Kernel Support Vector Machines (KSVMs) (← links)
- Layers API (tf.layers) (← links)
- Graph (← links)
- Graph execution (← links)
- Group attribution bias (← links)
- Hallucination (← links)
- Hashing (← links)
- Heuristic (← links)
- Hinge loss (← links)
- Holdout data (← links)
- Hyperplane (← links)
- Implicit bias (← links)
- In-group bias (← links)
- Incompatibility of fairness metrics (← links)
- Independently and identically distributed (i.i.d) (← links)
- Individual fairness (← links)
- Instance (← links)
- Inter-rater agreement (← links)
- Item matrix (← links)
- Items (← links)
- Least squares regression (← links)
- Logits (← links)
- Mean Absolute Error (MAE) (← links)
- Mean Squared Error (MSE) (← links)
- Metrics API (tf.metrics) (← links)
- Momentum (← links)
- NaN trap (← links)
- NumPy (← links)
- Loss surface (← links)
- Matplotlib (← links)
- Matrix factorization (← links)
- Metric (← links)
- Mini-batch stochastic gradient descent (← links)
- Minimax loss (← links)
- Model capacity (← links)
- Model training (← links)
- Multi-class logistic regression (← links)
- Multinomial classification (← links)
- Multinomial regression (← links)
- Node (TensorFlow graph) (← links)
- Noise (← links)
- Non-response bias (← links)
- Novelty detection (← links)
- Objective (← links)
- Objective function (← links)
- One-shot learning (← links)
- PR AUC (area under the PR curve) (← links)
- Parameter Server (PS) (← links)
- SavedModel (← links)
- Saver (← links)
- Operation (op) (← links)
- Optimizer (← links)
- Out-group homogeneity bias (← links)
- Outlier detection (← links)
- Outliers (← links)
- Oversampling (← links)
- Parameter update (← links)
- Partial derivative (← links)
- Participation bias (← links)
- Partitioning strategy (← links)
- Perceptron (← links)
- Performance (← links)
- Pipeline (← links)
- Pre-trained model (← links)
- Precision-recall curve (← links)
- Precision (← links)
- Prediction bias (← links)
- Predictive parity (← links)
- Predictive rate parity (← links)
- Preprocessing (← links)
- Prior belief (← links)
- Probabilistic regression model (← links)
- Proxy (sensitive attributes) (← links)
- Quantile (← links)
- Quantile bucketing (← links)
- Quantization (← links)
- Queue (← links)
- Rank (Tensor) (← links)
- Rank (ordinality) (← links)
- Ranking (← links)
- Re-ranking (← links)
- Recall (← links)
- Recommendation system (← links)
- Reporting bias (← links)
- Representation (← links)
- Ridge regularization (← links)
- Root directory (← links)
- Sampling bias (← links)
- Scalar (← links)
- Scaling (← links)
- Scikit-learn (← links)
- Scoring (← links)
- Selection bias (← links)
- Self-supervised learning (← links)
- TPU (← links)
- TPU Pod (← links)
- TPU chip (← links)
- TPU device (← links)
- TPU master (← links)
- TPU node (← links)
- TPU resource (← links)
- TPU slice (← links)
- TPU type (← links)
- TPU worker (← links)
- Tensor (← links)
- TensorBoard (← links)
- TensorFlow (← links)
- TensorFlow Playground (← links)
- TensorFlow Serving (← links)
- Tensor Processing Unit (TPU) (← links)
- Tensor rank (← links)
- Tensor shape (← links)
- Tensor size (← links)
- Wasserstein loss (← links)
- Weighted Alternating Least Squares (WALS) (← links)
- Self-training (← links)
- Semi-supervised learning (← links)
- Sensitive attribute (← links)
- Serving (← links)
- Shape (Tensor) (← links)
- Sparsity (← links)
- Squared hinge loss (← links)
- Step (← links)
- Step size (← links)
- Structural risk minimization (SRM) (← links)
- Summary (← links)
- Target (← links)
- Temporal data (← links)
- Test set (← links)
- Tf.Example (← links)