Even though computers can't read, they're very effective at extracting information from natural language text. They can determine the main themes in the text, figure out if the writers of the text have positive or negative feelings about what they've written, decide if two documents are similar, add labels to documents, and more.
Reactive programming is shaping the future of how we model data. With reactive, not only can you concisely wrangle and analyze static data, you can effectively work with data as a real-time infinite feed. Reactive Extensions (Rx) first gained traction in 2009 and has been ported to over a dozen major languages and platforms.
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Make your applications attack-proof by penetration testing with Python
Git has emerged as the leading revision control system for open source projects. Git is a distributed revision control and source code management (SCM) system with an emphasis on speed.
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Computational computing can be a complex topic. How to perform various mathematical functions in code isn't straight forward. With Python's Scipy library, we'll walk through a number of examples showing exactly how to create and execute complex computational computing functions.