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Spring Microservices: Internet-scale architecture with Spring framework, Spring Cloud, Spring Boot - Softcover
Inhaltsangabe
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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Über die Autorin bzw. den Autor
Anand Deshpande is the Director of big data delivery at Datametica Solutions. He is responsible for partnering with clients on their data strategies and helps them become data-driven. He has extensive experience with big data ecosystem technologies. He has developed a special interest in data science, cognitive intelligence, and an algorithmic approach to data management and analytics. He is a regular speaker on data science and big data at various events.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
- VerlagPackt Publishing
- Erscheinungsdatum2016
- ISBN 10 1786466686
- ISBN 13 9781786466686
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten436
- Kontakt zum HerstellerNicht verfügbar
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9781786466686
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