This is the code repository for Introduction to Artificial Intelligence with Java [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Introduction to Artificial Intelligence Using Java aims to demonstrate how to build AI Applications using Java. Starting out with search algorithms, game playing and knowledge-based systems, it’ll quickly dive into setting up with necessary tools required to program these techniques. Next, we shall build upon machine learning applications using Weka. We shall work with datasets by converting their formats, training and evaluation of classifiers, saving and loading classifiers. Next, we shall be working with training clusters and evaluating them. Next we shall develop and predict semi-supervised models.
- Get to grips with the different aspects of Artificial Intelligence
- Leverage different Java packages and tools such as WEKA, Rapidminer, deeplearning4j, and more
- Create machine-learning models using supervised and unsupervised machine learning techniques
- Understand logic programming and how to use it
- Implement different deep learning algorithms in deeplearning4j and build applications based on it
- Understand the basics of heuristic searching and genetic programming
- Differentiate between syntactic and semantic similarity between texts
- Perform sentiment analysis for effective decision-making with Lingpipe
To fully benefit from the coverage included in this course, you will need:
● Prior working knowledge of the Java programming language
● Familiarity with Git and GitHub for source control
● An understanding of basic Artificial Intelligence
This course has the following software requirements:
● NetBeans 8.2
● Weka 3.8
● SWI-Prolog 7.6
This course has been tested on the following system configuration:
● OS: Windows 7, Windows 10, MacOS, Ubuntu Linux 16.04 LTS
● Processor: Dual Core 3.0 Ghz
● Memory: 4GB
● Hard Disk Space: 200MB
● Video Card: NA