Artificial Intelligence Table of Contents


Table of Content
 


INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND JAVA

  • The Course Overview
  • Understanding AI Problems Related to Supervised/Unsupervised Learning
  • Difference between Classification and Regression
  • Installing JDK and JRE
  • Setting Up of Netbeans IDE
  • Import Java Libraries and Export Code Projects as JAR Files

EXPLORING SEARCH

  • Introduction to Search
  • Implementation of Dijkstra’s Search
  • Understand the Notion of Heuristics
  • Brief Introduction of A* Algorithm
  • Implementation of A* Algorithm

AI GAMES AND RULE BASED SYSTEM

  • Introduction of Min-Max Algorithm
  • Implementation of Min-Max Algorithm Using an Example
  • Installing Prolog
  • Introduction of Rule-Based Systems with Prolog
  • Setting Up the Prolog with Java
  • Executing Prolog Queries Using Java

INTERFACING WITH WEKA

  • Brief Introduction to Weka
  • Installing and Interfacing with Weka
  • Reading and Writing Datasets
  • Converting Datasets

HANDLING ATTRIBUTES

  • Filtering Attributes
  • Discretizing Attributes
  • Attribute Selection

SUPERVISED LEARNING

  • Developing a Classifier
  • Model Evaluation
  • Making Predictions
  • Saving/Loading Models

SEMI-SUPERVISED AND UNSUPERVISED LEARNING

  • Working with K-means Clustering
  • Evaluating a Clustering Model
  • Introduction to Semi-Supervised Learning
  • Difference Between Unsupervised and Semi-Supervised Learning
  • Self-training/Co-training Machine Learning Models
  • Making Predictions with Semi-Supervised Machine Learning Models



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