![]() The language allows a programmer to work in both object-oriented, and functional programming. Scala set out to create a new JVM-based language that avoids nearly all of these issues. Parralelism and and weirdly declaritive language for what one is writing also add to the confusion of some design choices with this language. I digress, one big problem was that the paradigm was rather strictly object-oriented and did not really have many multi-paradigm aspects. ![]() That being said, not everyone works with ridiculous complex numbers like I do for fun. The biggest problem I have with the language personally is with JVM itself and is with floating-point design. While Java is certainly an awesome language, there certainly are problems that the language has. I think this is for good reason, Java is a super cool platform that is rather new but still quite venerable. We are still feeling the impact of the boom that was Java back then. If you are familiar with Java, you might realize that 2004 was an absolute exploding prime-time for the language. The language was birthed in order to try to mitigate some of the criticism’s of the Java programming language. Scala is a programming language originally released in 2004 17 years ago. ![]() That in mind, if we would like to really understand where Scala is the industry, we will likely need to start from the beginning. When it comes to Data Science, Scala has had a somewhat similar story to the R programming language, only it is a lot younger. One language that has been used a lot in the past and is still used today is Scala. Before the luxurious, full-featured ecosystems and programming languages of today, things like Data Science used to be significantly different.
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