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Anway Jun 27, 2018

Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques This book bridges a big gap between today's technology and tomorrow's outlook and enables technologists to take a leap into the future. Ideal for developers, designers, data science enthusiast to get started into the journey of Artificial intelligence in the world of big data. Anand very articulately carries the reader right from the beginning concepts of big data, artificial intelligence, machine learning, natural language processing, using statistical methods, etc. into the very intricate details of the technology. Anand has also included snippets of sample code in almost every chapter, while explaining the practical usage of every aspect of the theories he puts forward. The author has kept the book structure very simple with starting from absolute basics of the concept as observed in day-to-day life, moving on to how technology takes inspiration from life, moving on how technology can solve those life problems. At the end of every chapter, the author gives FAQs about the chapter, which basically serve as a synopsis of the chapter, giving the reader a quick revision of what he/she learned in the chapter. And after the FAQs, the author ends the chapter summarizing what was discussed in that chapter and quickly sets up the context of the next chapter.

Amazon Verified review

Avadhoot Aug 24, 2018

This is very handy book for data engineers. With the advances in Machine Learning and AI, almost all applications are now getting powered by ML. Typically, there are data scientists who study the data and put together the representative models using Python + Jupyter combination. However, when these models (building and execution) need to be put into production, the traditional 'Data Engineers' need to rewrite this whole code in Big Data technologies and also be responsible for its lifecycle management. What I like about this book is that it explains all the concepts (data acquisition, representation, storage, preprocessing, ML algorithms, accuracy measurement, parameter tuning, pipelining etc) keeping Big Data eco system in mind. All the code examples use Spark and SparkML and implemented in Java which are the most reliable and performant technologies for Big Data Analytics.The other good thing about this book is that it explains the theory in a very systematic manner but does not stop at theory. Each chapter has several practical examples and FAQs which are very useful too. Finally, the whole process is effectively explained using the Cyber Security as a case study.I think the best use of this book is to 1. Scan through it once to understand the whole gambit of things 2. Keep it as a reference book when you are solving some real problems using Big Data, AI and ML.

Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques

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