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Spring Microservices: Internet-scale architecture with Spring framework, Spring Cloud, Spring Boot - Softcover

 
9781786466686: Spring Microservices: Internet-scale architecture with Spring framework, Spring Cloud, Spring Boot

Synopsis

Build next-generation Artificial Intelligence systems with Java

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using neural networks, NLP, and reinforcement learning

Book Description

In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data.

With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems.

By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems.

What you will learn

  • Manage Artificial Intelligence techniques for big data with Java
  • Build smart systems to analyze data for enhanced customer experience
  • Learn to use Artificial Intelligence frameworks for big data
  • Understand complex problems with algorithms and Neuro-Fuzzy systems
  • Design stratagems to leverage data using Machine Learning process
  • Apply Deep Learning techniques to prepare data for modeling
  • Construct models that learn from data using open source tools
  • Analyze big data problems using scalable Machine Learning algorithms

Who this book is for

This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

"synopsis" may belong to another edition of this title.

About the Author

Rajesh RV is a seasoned IT architect with extensive experience in diversified technologies and more than 16 years of airline IT experience. Rajesh received a degree in computer engineering from University of Cochin, India. He joined the JEE community Spring during the early days of EJB. During the course, as an architect, he worked on many large-scale, mission-critical projects, including New Generation Airline Passenger Reservation System (iFlyRes) and Next Generation Airline Cargo Reservation systems (Skychain and CROAMIS) in the airlines domain. At present, working as chief architect at Emirates (http://www.emirates.com/), Rajesh is handling the solution architecture portfolio, which is spread across various architecture capabilities, such as JEE, SOA, NoSQL, IoT, mobile, UI, integration, and more. At Emirates, Open Travel Platform (OTP) architected by Rajesh earned the group the prestigious 2011 RedHat Innovation Award in the Carved Out Costs category. In 2011, he introduced the innovative concept of the Honeycomb architecture based on the hexagonal architecture pattern used to transform the legacy mainframe system. Rajesh has a deep passion for technology and architecture. He also holds several certifications, such as BEA Certified WebLogic Administrator, Sun Certified Java Enterprise Architect, Open Group Certified TOGAF Practitioner, Licensed ZapThink Architect in SOA, and IASA global CITA-A Certified Architecture Specialist. Previously, Rajesh reviewed the book Service Oriented Java Business Integration, Packt Publishing by Binildas A. Christudas. Rajesh's social profile is available at https://www.linkedin.com/in/rajeshrv.

"About this title" may belong to another edition of this title.

  • PublisherPackt Publishing
  • Publication date2016
  • ISBN 10 1786466686
  • ISBN 13 9781786466686
  • BindingPaperback
  • LanguageEnglish
  • Number of pages436

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus. Seller Inventory # 9781786466686

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