AI world with AR
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X-OR learning | Artificial Intelligence

Hopfield network-working with example.

Associative Memory Networks | AI

Boltzmann learning | Artificial Intelligence

Learning Rules/Mechanisms of Neural Network

Perceptron and its learning | Artificial Intelligence

Selection of loss functions in NN | Artificial Intelligence

Usage of activations functions | Artificial Intelligence

Working of Neural Network, bias in NN | Artificial Intelligence

Neural network architecture and types | Artificial Intelligence

Backpropagation and learning process in Neural network | Artificial Intelligence

Artificial neuron | MC-Culloh Pit's model | artificial intelligence

alpha-beta pruning with example in Artificial Intelligence

Adversarial Search | minimax algorithm | Artificial Intelligence

Bayesian Belief Network | Artificial Intelligence

Knowledge Representation in uncertainty- Naive Bayes theorem | Artificial Intelligence

Backward chaining | Artificial Intelligence

Inference Engine: Forward Chaining | Artificial Intelligence

synchronic rules for inference | Artificial-Intelligence

Higher-order-logic representation | Artificial Intelligence

Wumpus world problem | Artificial Intelligence

Skolemization | Artificial intelligence

Resolution-in-First-order-logic | steps-in-resolution | Artificial-intelligence

Unification in FOL | Algorithm and examples. #UnificationInFOL#UnificationExamples#unificationInAI

Unification-in-first-order-logic | Artificial Intelligence #unification#FirstOrderLogic#AIBasics

Inference-in-First-order-logic | Artificial Intelligence #InferenceInFol#FirstOrderLogic#AIBasics

First-order-logic in KR| syntax and semantics| Artificial Intelligence #FirstOrderLogic#SyntaxInFOL

Rules of Inference | AI | logic in AI #RulesOfInference#LogicInAI

Propositional logic-characteristics, syntax and limitations of PL|AI #PropositionalLogic#properties

Knowledge representation and reasoning-types, cycle, requirements, techniques, approach, issues-KRR