Corresponding Sense
Corresponding Sense

Author: Brook W.R. Pearson

Publisher: BRILL

Published: 2021-10-01

Total Pages: 398

ISBN-13: 900449362X

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Corresponding Sense represents a turning point in the application of ‘hermeneutics’ to New Testament texts. Following the example of Hans-Georg Gadamer’s ‘philosophical hermeneutics’, Pearson treats several different problems in New Testament interpretation centred around the figure of Paul. In so doing, he demonstrates how a dialogical approach to the interpretation of ancient texts functions pragmatically to allow for a deeper understanding not only of individual texts, but also of their siting with the larger dialectical web of the texts and contexts of the ancient world. This approach, developed here in connection with the New Testament, also has relevance to other literature. In Corresponding Sense, Pearson outlines what he calls a ‘dialectical topography’—the tracing of connections and disjunctions between texts and their subject matter both within and outside of the New Testament. He uses both theoretical and practical discussion to demonstrate this approach, showing how it functions as a new way of approaching a Paul who is a member of a much larger community than simply the Judaism of his fathers—a Paul who participates in cultural narratives which extend throughout not only earliest Christianity, but also into the wider thought-world of the Roman Empire.

Artificial Intelligence for Big Data
Artificial Intelligence for Big Data

Author: Anand Deshpande

Publisher: Packt Publishing Ltd

Published: 2018-05-22

Total Pages: 371

ISBN-13: 1788476018

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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.