Machine Learning Fundamentals
The core vocabulary of machine learning, defined for revenue leaders rather than researchers.
- Activation Functions
- Active Learning
- Anomaly Detection
- Artificial General Intelligence (AGI)
- Association Rules
- Attention Mechanism
- Automated Machine Learning (AutoML)
- Bayesian Networks
- Bias-Variance Tradeoff
- Classification
- Closed Model
- Clustering
- Cognitive Architectures
- Collaborative Filtering
- Decision Trees
- Deep Learning
- Dimensionality Reduction
- Emergent Capabilities
- Ensemble Methods
- Federated Learning
- Graph Neural Networks (GNNs)
- K-Means Clustering
- Latent Space
- Machine Learning
- Meta-Learning
- Mixture of Experts (MoE)
- Neural Network
- Neuro-Symbolic AI
- One-Shot Learning
- Open Source Models
- Perceptron
- Random Forest
- Recurrent Neural Network (RNN)
- Regression
- Reinforcement Learning (RL)
- Semi-Supervised Learning
- Supervised Learning
- Transformer
- Turing Test
- Unsupervised Learning
- Weight
- XGBoost