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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