Topic hub
Machine Learning
Algorithms and methods that enable systems to learn from data.
391 dictionary entries in this topic
All terms A–Z
391 terms · A–Z
A
B
C
- candidate generation
- categorical data
- centroid
- centroid-based clustering
- Character N-gram F-score
- citation precision
- citation recall
- class
- class-balanced dataset
- class-imbalanced dataset
- Classification
- classification model
- classification threshold
- classifier
- clipping
- Clustering
- co-adaptation
- co-training
- collaborative filtering
- compact model
- concept drift
- condition
- configuration
- confirmation bias
- confusion matrix
- continuous feature
- convenience sampling
- convergence
- convex set
- cost
- counterfactual fairness
- critic
- cross-entropy
- cross-validation
- cumulative distribution function
D
- data analysis
- Data Augmentation
- data parallelism
- data set or dataset
- decision boundary
- decision forest
- decision threshold
- decision tree
- deep model
- demographic parity
- denoising
- dense feature
- dense layer
- depth
- derived label
- discrete feature
- discriminative model
- disparate impact
- disparate treatment
- distribution
- divisive clustering
- downsampling
- dropout regularization
- dynamic
- dynamic model
E
F
- F1
- fairness metric
- false negative
- false negative rate
- false positive
- false positive rate
- fast decay
- feature
- feature cross
- feature engineering
- feature extraction
- feature importances
- feature set
- feature spec
- feature vector
- featurization
- feedback loop
- few-shot learning
- Fine-tuning
- forget gate
- foundation model
- fraction of successes
- full softmax
G
H
I
- i.i.d.
- image recognition
- imbalanced dataset
- implicit bias
- imputation
- in-set condition
- incompatibility of fairness metrics
- independently and identically distributed
- individual fairness
- Inference
- inference path
- information gain
- input layer
- instance
- inter-rater agreement
- interpretability
- items
- iteration
K
L
- L0 regularization
- L1 loss
- L1 regularization
- L2 loss
- L2 regularization
- label
- label leakage
- labeled example
- lambda
- landmarks
- language model
- layer
- leaf
- Learning Interpretability Tool
- learning rate
- least squares regression
- Levenshtein Distance
- linear
- linear model
- linear regression
- LLM evaluations
- Log Loss
- log-odds
- logistic regression
- logits
- LoRA
- loss
- loss aggregator
- loss curve
- loss function
M
- Machine Learning
- majority class
- MBPP
- Mean Absolute Error
- mean average precision at k
- Mean Squared Error
- metric
- mini-batch
- minimax loss
- minority class
- modality
- model
- model capacity
- model cascading
- model parallelism
- model router
- model training
- multi-class classification
- multi-class logistic regression
- multimodal instruction-tuned
- multimodal model
- multinomial classification
- multinomial regression
- multitask
N
O
P
- packed data
- parameter
- partitioning strategy
- pass at k
- performance
- permutation variable importances
- perplexity
- pipeline
- pipelining
- positive class
- post-processing
- PR AUC
- precision
- precision at k
- precision-recall curve
- prediction
- prediction bias
- predictive parity
- predictive rate parity
- prior belief
- probabilistic regression model
- probability density function
- provenance
- proxy
- proxy labels
Q
R
- R-squared
- random forest
- rank
- ranking
- rater
- re-ranking
- recall
- recall at k
- Rectified Linear Unit
- regression model
- regularization
- regularization rate
- ReLU
- representation
- retrieval-augmented generation
- ROC (receiver operating characteristic) Curve
- root
- Root Mean Squared Error
- rotational invariance
- ROUGE
- ROUGE-L
- ROUGE-N
- ROUGE-S
S
- sampling with replacement
- scalar
- scaling
- scoring
- self-supervised learning
- self-training
- semi-supervised learning
- sensitive attribute
- sentiment analysis
- sequence model
- sequence-to-sequence task
- serving
- shrinkage
- sigmoid function
- similarity measure
- single program / multiple data
- size invariance
- sketching
- softmax
- sparse feature
- sparse representation
- sparse vector
- sparsity
- spatial pooling
- split
- splitter
- squared hinge loss
- squared loss
- state-action value function
- static
- static inference
- stationarity
- step size
- stochastic gradient descent
- structural risk minimization
- subsampling
- Supervised Learning
- supervised machine learning
- synthetic feature
T
- target
- task
- temperature
- temporal data
- Tensor rank
- Tensor shape
- Tensor size
- test
- test loss
- test set
- text span
- threshold
- time series analysis
- top-k accuracy
- toxicity
- training
- training loss
- training set
- training-serving skew
- transfer learning
- translational invariance
- true negative
- true positive
- true positive rate
U
V
W
X
Z
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Key Machine Learning concepts
A/B testing
A method of comparing two versions of a product or service to determine which one performs better
ablationA technique used to remove or disable parts of a machine learning model to understand their importance
accuracyThe degree to which a model's predictions match the actual outcomes
activation functionA mathematical function that introduces non-linearity into a neural network model
active learningA machine learning approach where the model actively selects the most informative data to learn from
adaptationThe process of adjusting to new or changing conditions
agglomerative clusteringA type of hierarchical clustering that groups similar data points together
anomaly detectionThe process of identifying data points that do not conform to expected patterns or behaviors