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Machine Learning
Glossary
Browse our glossary to learn about the techniques and technologies being used in the world of artificial intelligence, machine learning, computer vision and active learning.
All
A
B
C
D
E
F
G
H
I
K
L
M
N
O
P
Q
R
S
T
U
V
Z
A
Active Learning
AI Assisted Labeling
Alphapose
Anchor Boxes
Anomaly Detection
Annotation
Artificial Intelligence
B
Bias
Blur
Bounding Box
C
ChatGPT
Classification
Class Boundary
Class Imbalance
Convolutional Neural Network (CNN)
COCO
Computer Vision
Computer Vision Model
Computer Vision Ontology
Concept Drift
Confusion Matrix
Calibration Curve
D
Data Approximation
Data Augmentation
Data Error
Data Drift
Data Operations
Data Quality
Datasets
Debug
Decision Tree
Deep Learning
DICOM
Dynamic And Event-Based Classifications
E
Edge Detection
Epochs
F
F1 Score
False Positive Rate
Features
Feature Extraction
Feature Vector
Few Shot Learning
Frames Per Second (FPS)
G
Generative Pre-Trained Transformer (GPT)
Ghost Frames
Greyscale
Ground Truth
H
Human In The Loop (HITL)
Human Pose Estimation
Hyperparameters
I
Image Annotation
Image Degredation
Imbalanced Dataset
Instance Segmentation
Interpolation
Intersection over Union (IoU)
K
Keypoints
K-Means Clustering
L
Label
Label Errors
Learning Rate
Lifecycle
M
Mean Average Precision (mAP)
Medical Image Segmentation
Machine learning
ML Ops
Model Accuracy
Model Parameters
Model Validation
Mean Square Error (MSE)
N
Neural Networks
NIfTI
NLP
Named Entity Recognition (NER)
Noise
Normalization
O
Object Detection
Object Localization
Object Tracking
One-Shot Learning
Openpose
Outlier detection
Overfitting
P
PACS
Panoptic Segmentation
Pool based Sampling
Pre Trained Model
Precision
Population Stability Index (PSI)
Q
Query Strategy
Query Synthesis Methods
R
Random Forest
Recall
Region-Based CNN
Regression
Reinforcement Learning
ROC
S
Scale Imbalance
Segment Anything Model (SAM)
Stream-based Sampling
Supervised Learning
T
Training Data
Transfer Learning
Transformers
Triplet Loss
True Positive Rate (TPR)
Type 1 Errors
Type 2 Errors
U
Unsupervised Learning
V
Variance
Z
Zero Shot Learning