Machine Learning Glossary
- Algorithm
- Artificial Intelligence (AI)
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Neural Networks
- Deep Learning
- Decision Trees
- Random Forests
- Support Vector Machines (SVM)
- Gradient Descent
- Backpropagation
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Long Short-Term Memory (LSTM)
- Generative Adversarial Networks (GAN)
- Overfitting
- Underfitting
- Cross-Validation
- Bias-Variance Tradeoff
- Feature Engineering
- Feature Selection
- Dimensionality Reduction
- Principal Component Analysis (PCA)
- Clustering
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Spatial Clustering of Applications with Noise (DBSCAN)
- Anomaly Detection
- Data Preprocessing
- Normalization
- Standardization
- Training Set
- Test Set
- Validation Set
- Batch Learning
- Online Learning
- Transfer Learning
- Multi-task Learning
- End-to-End Learning
- Model Evaluation
- Accuracy
- Precision
- Recall
- F1 Score
- Area Under the ROC Curve (AUC-ROC)
- Confusion Matrix
- Hyperparameter Tuning
- Grid Search
- Random Search
- Learning Rate
- Loss Function
- Cost Function
- Mean Squared Error (MSE)
- Cross-Entropy
- Regularization
- Dropout
- Batch Normalization
- Activation Function
- ReLU (Rectified Linear Unit)
- Sigmoid Function
- Tanh Function
- Softmax Function
- Embeddings
- Word2Vec
- GloVe (Global Vectors for Word Representation)
- Natural Language Processing (NLP)
- Tokenization
- Lemmatization
- Stemming
- Bag of Words
- TF-IDF (Term Frequency-Inverse Document Frequency)
- Sequence Modeling
- Attention Mechanism
- Transformer Models
- BERT (Bidirectional Encoder Representations from Transformers)
- GPT (Generative Pre-trained Transformer)
- Data Augmentation
- Synthetic Data Generation
- Ensemble Learning
- Boosting
- Bagging
- Stacking
- Meta-Learning
- Feature Extraction
- Autoencoders
- Variational Autoencoders (VAE)
- Reinforcement Learning Agents
- Q-Learning
- Policy Gradient Methods
- Deep Q-Network (DQN)
- Markov Decision Processes (MDP)
- State
- Action
- Reward
- Policy
- Exploration vs. Exploitation
- Monte Carlo Methods
- Temporal Difference Learning
- Semi-supervised Learning