Frameworks, libraries and languages for machine learning

It's no secret that building applications geared for artificial intelligence, machine learning and predictive analytics is a big challenge, even for the most experienced developers. Luckily, the amount of resources available to help both novice and expert programmers build sophisticated and intelligent software continues to grow. This includes major feature updates to popular application development platforms, a deluge of data-intensive algorithms created by open source developers, and an expanse of community-supported libraries. This is particularly true when it comes to the languages and frameworks that now directly target the requirements for developing machine learning applications. Not all of them are quite the same, however, and they vary in aspects that range from data handling capabilities to their associated tool sets.