Introduction to Artificial Intelligence with Java [Video]

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Introduction to Artificial Intelligence with Java [Video]

Nisheeth Joshi

Thursday, March 15, 2018

New Release!

Build real-world Artificial Intelligence applications with Java to intelligently interact with the world around you

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Video Details

ISBN 139781788474016

Course Length2 hours and 10 minutes

Video Description

Artificial Intelligence, increasingly relevant in the modern world where everything is driven by technology and data, is the process of automating any system or process to carry out complex tasks and functions automatically, in order to achieve optimal productivity.

This video explains the basics of AI using popular Java-based libraries and frameworks to build your smart applications. We will cover easy-to-complex artificial intelligence tasks such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation with the practical approach we mentioned earlier.

By the end of this video, you will have a solid understanding of Artificial Intelligence concepts. You will be able to build your own smart applications for multiple domains, as required.

Style and Approach

A step-by-step guide to building artificial intelligent solutions with Java

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

What You Will Learn

Get to grips with the different aspects of Artificial Intelligence
Leverage different Java packages and tools such as WEKA, Rapidminer, deeplearning4j, and more
Understand logic programming and how to use it
Create machine-learning models using supervised and unsupervised machine learning techniques
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

Authors

Nisheeth Joshi

Nisheeth Joshi is an Associate Professor and a Researcher at Banasthali University. He has also done a PhD in Natural Language Processing.

His areas of interest include Computational Linguistics, Natural Language Processing, and Artificial Intelligence. Besides this, he is also very actively involved in the development of MT engines. He is one of those experts empanelled within the TDIL Program, Department of Information Technology, Govt. of India, the premier organization that oversees Language Technology Funding and Research in India. He has several publications to his name in various journals and conferences and also serves on the program committees and editorial boards of several conferences and journals. LinkedIn - https://www.linkedin.com/in/nisheethjoshi/

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