Handson Artificial Intelligence With Java For Beginners 1st Nisheeth Joshi by Nisheeth Joshi 9781789537550, 178953755X instant download after payment.

Book Description:-
Artificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data. AI can be used for automating systems or processes to carry out complex tasks and functions in order to achieve optimal performance and productivity.
Hands-On Artificial Intelligence with Java for Beginners begins by introducing you to AI concepts and algorithms. You will learn about various Java-based libraries and frameworks that can be used in implementing AI to build smart applications.
In addition to this, the book teaches you how to implement easy to complex AI tasks, such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation, all with a practical approach.
By the end of this book, you will not only have a solid grasp of AI concepts, but you'll also be able to build your own smart applications for multiple domains.
What you will learn:-
* Leverage different Java packages and tools such as Weka, RapidMiner, and Deeplearning4j, among others
* Build machine learning models using supervised and unsupervised machine learning techniques
* Implement different deep learning algorithms in Deeplearning4j and build applications based on them
* Study the basics of heuristic searching and genetic programming
* Differentiate between syntactic and semantic similarity among texts
* Perform sentiment analysis for effective decision making with LingPipe
Who this book is for:-
Hands-On Artificial Intelligence with Java for Beginners is for Java developers who want to learn the fundamentals of artificial intelligence and extend their programming knowledge to build smarter applications.
Table of Contents:-
1. Introduction to Artificial Intelligence and Java
2. Exploring Search
3. AI Games and Rule Based System
4. Interfacing with Weka
5. Handling Attributes
6. Supervised Learning
7. Semi-Supervised and Unsupervised Learning