Machine learning can be broken down into several categories, including supervised, unsupervised, semi-supervised and reinforcement learning.
While supervised learning relies on labeled input data in order to infer its relationships with output results, unsupervised learning detects patterns among unlabeled input data.
Semi-supervised learning employs a combination of both methods, and reinforcement learning motivates programs to repeat or elaborate on processes with desirable outcomes while avoiding errors.
Enabled with both low and high-level programming ability, C++ allows for a higher level of control and efficiency than other programming languages in machine learning contexts.
Developed by Sun Microsystems in the mid-1990s, Java was originally built to be a high-level and object-oriented programming language that looks and feels similar to C++. Along with being extremely popular, Java can implement a wide variety of algorithms, which are very useful to the machine learning community.
Out of all of the programming languages being applied to machine learning, Python remains the most popular.
Although human programming will never go extinct, programming for machine learning will likely become less focused on code in coming years, as machines are trained to code themselves.
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