The document displays a calendar for the year with the months of January, April, July, and October shown. Each month is displayed across four rows with the days of the month numbered in each box.
identify and create value through data analytics across the credit cycle in consumer credit. Presentation at EFMA consumer credit conference by george georgakopoulos
FRIENDS briefs members of the House of Commons Heritage Committee on a new survey which finds strong support for the CBC and widespread belief that the Conservative government is hostile to the public broadcaster.
Graphs, Edges & Nodes - Untangling the Social WebJoël Perras
Many of the most popular web applications today deal with highly organized and structured data that represent entities, and the relationships between these entities. LinkedIn can tell you how many degrees of separation there are between yourself and the CEO of Samsung, Facebook can figure out people that you might already know, Digg can recommend article submissions that you might like, and LastFM suggests music based on your current listening habits.
We’ll take a look at the basic theory behind how some of these features can be implemented (no computer science degree required!), and then dig in to a few practical implementations using PHP & and a relational database, as well as with Redis. Lastly, we’ll take a quick look at the current landscape of graph-based datastores that simplify many of these operations.
identify and create value through data analytics across the credit cycle in consumer credit. Presentation at EFMA consumer credit conference by george georgakopoulos
FRIENDS briefs members of the House of Commons Heritage Committee on a new survey which finds strong support for the CBC and widespread belief that the Conservative government is hostile to the public broadcaster.
Graphs, Edges & Nodes - Untangling the Social WebJoël Perras
Many of the most popular web applications today deal with highly organized and structured data that represent entities, and the relationships between these entities. LinkedIn can tell you how many degrees of separation there are between yourself and the CEO of Samsung, Facebook can figure out people that you might already know, Digg can recommend article submissions that you might like, and LastFM suggests music based on your current listening habits.
We’ll take a look at the basic theory behind how some of these features can be implemented (no computer science degree required!), and then dig in to a few practical implementations using PHP & and a relational database, as well as with Redis. Lastly, we’ll take a quick look at the current landscape of graph-based datastores that simplify many of these operations.