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.

�ber 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.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

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