The key lesson of this session, presented by Lino Ramirez, is that it’s all about empowering people. Perl gives us the power to empower people.
I really enjoyed the video of a tae kwon do match as a real-world analog of software development. Try one technique, see the result (get hit); try another technique, see the result (get knocked down); ad infinitum.
There are three phases: preparation, modeling, and implementation. These phases are not linear in nature. One moves between phases as necessary to design the solution.
As he delved into the case studies, I started to zone out, so I have little to say about his examples of machine learning and Perl in action. I wanted to enjoy this session more, since I’ve often wanted to get back into using neural networks and other machine learning techniques in my code. Unfortunately, I just found it too difficult to follow his case studies. Still, I have some good pointers for packages that will help me sprinkle some machine learning goodness in my code.
I like his conclusion: “Perl excels at empowering people in all three phases of the development of a machine learning application.” Perl is awesome for rapid application development, which in turn gets solutions to people who need them faster.