Grant Ingersoll

Lucene Boot Camp
Apache Lucene is a high-performance, cross-platform search API in production use in a large number of applications. This tutorial will be an in-depth, hands-on class targeted at developers who wish to integrate Lucene Java into their applications. The two day tutorial will cover the key concepts behind Lucene, along with code examples, documentation and resources. Concepts covered are: Lucene setup; indexing content, indexing customization; searching, including how to use the many Lucene Query APIs to achieve better search results. Additionally, we will cover advanced topics like Lucene performance and threading issues, Span Queries, filters, term vectors, and sorting, all of which can help solve common problems in search applications. The class will gain hands-on experience with Lucene and leave with the know-how to build a Lucene-based application. No prior Lucene knowledge is required, but participants must be able to code in the Java programming language and come prepared to code. Concepts learned can also be applied to Solr. Students are encouraged to bring their own content to index/search. Please refer to the Lucene Boot Camp website (http://www.lucenebootcamp.com) for more information on the class.
Apache Lucene is a high-performance, cross-platform search API in production use in a large number of applications. This tutorial will be an in-depth, hands-on class targeted at developers who wish to integrate Lucene Java into their applications. The two day tutorial will cover the key concepts behind Lucene, along with code examples, documentation and resources. Concepts covered are: Lucene setup; indexing content, indexing customization; searching, including how to use the many Lucene Query APIs to achieve better search results. Additionally, we will cover advanced topics like Lucene performance and threading issues, Span Queries, filters, term vectors, and sorting, all of which can help solve common problems in search applications. The class will gain hands-on experience with Lucene and leave with the know-how to build a Lucene-based application. No prior Lucene knowledge is required, but participants must be able to code in the Java programming language and come prepared to code. Concepts learned can also be applied to Solr. Students are encouraged to bring their own content to index/search. Please refer to the Lucene Boot Camp website (http://www.lucenebootcamp.com) for more information on the class.
Apache Lucene is a high-performance, cross-platform search API in production use in a large number of applications. This tutorial will be an in-depth, hands-on class targeted at developers who wish to integrate Lucene Java into their applications. The two day tutorial will cover the key concepts behind Lucene, along with code examples, documentation and resources. Concepts covered are: Lucene setup; indexing content, indexing customization; searching, including how to use the many Lucene Query APIs to achieve better search results. Additionally, we will cover advanced topics like Lucene performance and threading issues, Span Queries, filters, term vectors, and sorting, all of which can help solve common problems in search applications. The class will gain hands-on experience with Lucene and leave with the know-how to build a Lucene-based application. No prior Lucene knowledge is required, but participants must be able to code in the Java programming language and come prepared to code. Concepts learned can also be applied to Solr. Students are encouraged to bring their own content to index/search. Please refer to the Lucene Boot Camp website (http://www.lucenebootcamp.com) for more information on the class.
With the massive rise in both structured and unstructured data comes the need to better understand what is in the data. Machine Learning algorithms are often designed to make sense of large volumes of data with minimal human input. In this talk, we cover some of the basic algorithms of machine learning (without all the gory math) and show how the new Apache Mahout project is attempting to solve these problems in a scalable way by utilizing Hadoop.