Artificial Intelligence & Machine Learning Glossary

Welcome to the ultimate Artificial Intelligence & Machine Learning Glossary, your comprehensive resource for demystifying the complex world of AI and ML.

Whether you’re a student embarking on your journey, a professional seeking to deepen your understanding, or simply an AI enthusiast curious about the latest in technology, this glossary is designed to provide you with a clear understanding of key terms and concepts in the rapidly evolving fields of Artificial Intelligence and Machine Learning.

A

• Algorithm
• Artificial Intelligence (AI)
• Artificial Neural Networks (ANN)
• Activation Function

B

• Backpropagation
• Batch Size
• Bias (Machine Learning)
• Big Data
• Binary Classification

C

• Chatbot
• Clustering
• Cognitive Computing
• Computer Vision
• Convolutional Neural Network (CNN)

D

• Data Mining
• Data Science
• Data Augmentation
• Dataset
• Deep Learning
• Decision Tree
• Dimensionality Reduction
• Dropout

E

• Embedding Layer
• Ensemble Learning
• Epoch
• Evolutionary Algorithms

F

• Feature Engineering
• Feature Extraction
• Feature Selection
• Federated Learning
• Feature Vector

G

• GAN (Generative Adversarial Network)
• Gradient Descent
• Gradient Boosting
• Graph Neural Networks (GNN)

H

• Hashing Vectorizer
• Heuristics
• Hyperparameter

I

• Image Recognition
• Imbalanced Data
• Inference

J

• Jupyter Notebooks

K

• Kernel (SVM)
• Knowledge Graph
• K-means Clustering

L

• Label
• Latent Variable
• Learning Rate
• Logistic Regression
• Long Short-Term Memory (LSTM)
• Loss Function

M

• Machine Learning (ML)
• Model
• Multi-class Classification

N

• Natural Language Processing (NLP)
• Neural Network
• Non-linear Activation

O

• Object Detection
• Outlier Detection
• Overfitting

P

• Parameter
• Pattern Recognition
• Pooling Layer
• Precision
• Predictive Analytics
• Principal Component Analysis (PCA)
• Probability Distribution

Q

• Q-learning
• Quantization
• Query Understanding

R

• Random Forest
• Recall
• Recommender Systems
• Recurrent Neural Network (RNN)
• Reinforcement Learning
• Regularization
• Regression
• Reinforcement Learning
• Reinforcement Signal
• ROC Curve

S

• Semantic Analysis
• Sentiment Analysis
• Sequence Modeling
• Stochastic Gradient Descent (SGD)
• Supervised Learning
• Support Vector Machine (SVM)

T

• TensorFlow
• Tokenization
• Transfer Learning
• Transformer Models

U

• Underfitting
• Unsupervised Learning

V

• Validation Set
• Variational Autoencoder (VAE)
• Vector Space Model

W

• Word Embedding
• Weight Initialization

X

• XAI (Explainable AI)
• Xavier Initialization

Z

• Zero-shot Learning