— Automated Programming
— Knowledge Representation
— Expert Systems
— Planning and Scheduling
— Speech Recognition
— Problem Solving & Search Strategies
— Visual Perception
— Natural Language Processing (NLP)
— Intelligent Robotics
— K-Means Clustering
— Principal Component Analysis (PCA)
— Decision Trees
— Automatic Reasoning
— Random Forest
— Ensemble Methods
— Naive Bayes Classification
— Support Vector Machines (SVM)
— K-Nearest Neighbors (KNN)
— Linear / Logistic Regression
— Multilayer Perceptrons (MLP)
— Boltzmann Machines
— Reinforcement Learning
— Anomaly Detection
— Speech Recognition
— Radial Basis Function Networks
— Recurrent Neural Networks (RNN)
— Autoencoders
— Self-Organizing Maps
— Hopfield Networks
— Adaptive Resonance Theory (ART)
— Multilayer Perceptrons (MLP)
— Convolutional Neural Networks (CNN)
— Recurrent Neural Networks (RNN)
— Generative Adversarial Networks (GAN)
— Deep Belief Networks (DBN)
— Long Short-Term Memory Networks (LSTM)
— Deep Reinforcement Learning
— Transformer Models (such as BERT, GPT)
— Deep Autoencoders
Here’s a list of AI techniques with sample applications and libraries:
- Sample: AI-assisted coding tools like GitHub Copilot suggest code snippets based on natural language descriptions, helping developers write code faster.
- Sample: Ontology-based systems used in medical diagnosis (e.g., SNOMED CT) represent medical knowledge, allowing AI systems to reason about diseases and treatments.