Ted Dunning: 5 books

Book cover of Streaming Architecture

Streaming Architecture

New Designs Using Apache Kafka and MapR Streams

by Ted Dunning, Ellen Friedman
Language: English
Release Date: May 10, 2016

More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World...
Book cover of Sharing Big Data Safely

Sharing Big Data Safely

Managing Data Security

by Ted Dunning, Ellen Friedman
Language: English
Release Date: September 15, 2015

Many big data-driven companies today are moving to protect certain types of data against intrusion, leaks, or unauthorized eyes. But how do you lock down data while granting access to people who need to see it? In this practical book, authors Ted Dunning and Ellen Friedman offer two novel and practical...
Book cover of Practical Machine Learning: Innovations in Recommendation
by Ted Dunning, Ellen Friedman
Language: English
Release Date: August 18, 2014

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settings—and demonstrates how even a small-scale development team can design...
Book cover of Real-World Hadoop
by Ted Dunning, Ellen Friedman
Language: English
Release Date: March 24, 2015

If you’re a business team leader, CIO, business analyst, or developer interested in how Apache Hadoop and Apache HBase-related technologies can address problems involving large-scale data in cost-effective ways, this book is for you. Using real-world stories and situations, authors Ted Dunning and...
Book cover of Practical Machine Learning: A New Look at Anomaly Detection
by Ted Dunning, Ellen Friedman
Language: English
Release Date: July 21, 2014

Finding Data Anomalies You Didn't Know to Look For Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what...
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