Search results for ""Author Trey Grainger""

DESCRIPTION Whether handling big data, building cloud-based services, or developing multi-tenant web applications, it's vital to have a fast, reliable search solution. Apache Solr is a scalable and ready-to-deploy open-source full-text search engine powered by Lucene. It offers key features like multi-lingual keyword searching, faceted search, intelligent matching, and relevancy weighting right out of the box. Solr in Action is the definitive guide to implementing fast and scalable search using Apache Solr 4. It uses well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. Readers will gain a deep understanding of how to implement core Solr capabilities such as faceted navigation through search results, matched snippet highlighting, field collapsing and search results grouping, spell checking, query auto-complete, querying by functions, and more. RETAIL SELLING POINTS Clearly-written comprehensive guide In-depth coverage of Solr 4 Uses real-world examples backed by years of experience AUDIENCE This book assumes some knowledge of Java and standard database technology. No prior experience with Solr or Lucene is required. ABOUT THE TECHNOLOGY Solr 4 provides new features to enable large-scale distributed search solutions that can be deployed as an elastically scaling cloud-based service and can provide additional intelligence to other big data technologies like Hadoop and Mahout.

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Learn statistics by analysing professional basketball data! Statistics Slam Dunk is an action-packed book that will help you build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. This textbook will upgrade your R data science skills by taking on practical analysis challenges based on NBA game and player data. You will take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. And just like in the real world, you will get no clean pre-packaged datasets in this book. You will develop a toolbox of R data skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Execute hypothesis tests, including t-tests and chi-square tests for independence Compute expected values, Gini coefficients, and z-scores Is losing games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Each chapter in this one-of-a-kind guide uses new data science techniques to reveal interesting insights like these. About the technology Amazing insights are hiding in raw data, and statistical analysis with R can help reveal them! R was built for data, and it supports modelling and statistical techniques including regression and classification models, time series forecasts, and clustering algorithms. And when you want to see your results, R's visualisations are stunning, with best-in-class plots and charts.

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