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Building data-driven web applications using R and Shiny

July 22, 2016 By editor

Learning Tree just published my article on using R and Shiny to build data-driven web applications. … [Read more...]

Filed Under: General

Microsoft Data Science Summit

July 22, 2016 By editor

Microsoft have a new conference aimed at data scientists. The first Microsoft Data Science Summit will be held between 26-27 September 2016 in Atlanta GA. The conference will cover ...the latest Big Data, Machine Learning, Artificial Intelligence, and Open Source techniques and technologies. … [Read more...]

Filed Under: Big data, Data science, Machine learning Tagged With: conference, Microsoft

R at Microsoft

July 17, 2016 By editor

David Smith, R Community Lead at Microsoft, talks about how they are using R. He covers both how it is being integrated into the product line and how it is used internally to analyse operational data. … [Read more...]

Filed Under: Data analysis, Data science, Machine learning Tagged With: Microsoft, R

Common use cases for graph databases

July 15, 2016 By editor

Neo4j have an informative whitepaper highlighting the top 5 use cases for graph databases. They highlight the following application areas Fraud detection Real-time recommendations Master data management Network and IT operations Identity and access management A similar article on Data Informed also highlights the role graph databases can play in managing the Internet of Things. … [Read more...]

Filed Under: Big data Tagged With: application, graph database, Neo4j, NoSQL, use case

RDDs, DataFrames and Datasets

July 14, 2016 By editor

There are now three Spark APIs for working with large volumes of data RDD DataFrame Dataset Which one should we use? Good question. Jules Damji provides a pretty comprehensive answer in an article on the Databricks blog. RDD was the original API for working with large volumes of data. The first thing to note is that the RDD API is not being deprecated. It has an important role to play. RDDs … [Read more...]

Filed Under: Big data, Data science, Machine learning Tagged With: DataFrame, dataset, RDD, Spark

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