Preparing Your Company for Machine Learning
My last article on artificial intelligence (AI) and machine learning (ML) concluded that “the split of the necessary AI/ML between the ‘edge’ of corporate users and the software itself is still to be determined.” Several readers have reached out to ask about the tools and skills needed to accomplish the edge computing for their companies.
For many companies to take advantage of machine learning, they will require new skill sets. I’ll review some here that will work.
Wherever we go in terms of programming, it is unmistakable that math is making a comeback. I’m talking floating point arithmetic, deep statistics, and linear algebra. ML is the application of math to tasks. Without great competency in math, ML will remain elusive to the company or the individual.
Programming Languages for Machine Learning
For all of these languages, ML algorithms perform best on a GPU instead of a CPU.
C and C++ are programming staples at this point. Though difficult to use, creating many lines of code, and leaving the memory management to you, performance is undeniable when the code is well written. They are the closest realistic languages to bare metal programming, and you can implement ML with them.
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