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AL-504 (B) · Natural Language Processing/Official Syllabus

Natural Language Processing (AL-504 (B)) - Official Syllabus (AL-504)

1
Unit 1

UNIT-1 :

  • Introduction to Computational Intelligence (CI): Basics of CI History of CI
  • Adaptation Learning Self-Organization State Space Search and Evolution
  • CI and Soft Computing CI Techniques; Applications of CI;
  • Decision Trees: Introduction Evaluation Different splitting criterion
  • Implementation aspect of decision tree.
  • Neural Network: Introduction types issues implementation applications
2
Unit 2

UNIT-2 :

  • Fuzzy Set Theory: Fuzzy Sets Fuzzy Set Characteristics
  • Basic Definition and Terminology Fuzzy Operators Fuzzy Relations and Composition
  • Member Function Formulation Fuzzy Rules and Fuzzy Reasoning
  • Extension Fuzzy Inference Systems
  • Input Space Partitioning and Fuzzy Modeling.
  • Fuzziness and Defuzzification Fuzzy Controllers
  • Different Fuzzy Models: Mamdani Fuzzy Models Sugeno Fuzzy Models
  • Tsukamoto Fuzzy Models etc.
  • Neuro Fuzzy Modeling
  • Introduction to Neuro Fuzzy Control
3
Unit 3

UNIT-3 :

  • Rough Set Theory: Introduction Fundamental Concepts
  • Knowledge Representation Set Approximations and Accuracy
  • Vagueness and Uncertainty in Rough Sets
  • Rough Membership Function Attributes Dependency and Reduction
  • Application Domain Hidden Markov Model (HMM)
  • Graphical Models Variable Elimination Belief Propagation
  • Markov Decision Processes.
4
Unit 4

UNIT-4 :

  • Evolutionary Computation: Genetic Algorithms: Basic Genetics Concepts Working Principle Creation of Off springs
  • Encoding Fitness Function Selection Functions
  • Genetic Operators-Reproduction Crossover Mutation;
  • Genetic Modeling Benefits;
  • Problem Solving;
  • Introduction to Genetic Programming
  • Evolutionary Programming and Evolutionary Strategies.
5
Unit 5

UNIT-5 :

  • Swarm Intelligence: Introduction to Swarm Intelligence
  • Swarm Intelligence Techniques: Ant Colony Optimization (ACO): Overview ACO Algorithm;
  • Particle Swarm Optimization (PSO): Basics Social Network Structures PSO Parameters and Algorithm;
  • Grey wolf optimization(GWO);
  • Application Domain of ACO and PSO;
  • Bee Colony Optimization etc.;
  • Hybrid CI Techniques and applications;
  • CI Tools
6
Unit 6

== END OF UNITS==

  • ==End of Syllabus==
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