{"id":243,"date":"2020-09-01T12:27:06","date_gmt":"2020-09-01T16:27:06","guid":{"rendered":"https:\/\/www.macloo.com\/ai\/?p=243"},"modified":"2020-09-05T15:33:54","modified_gmt":"2020-09-05T19:33:54","slug":"free-courses-in-machine-learning","status":"publish","type":"post","link":"https:\/\/www.macloo.com\/ai\/2020\/09\/01\/free-courses-in-machine-learning\/","title":{"rendered":"Free courses in machine learning"},"content":{"rendered":"\n

Two days ago, I came upon this newly published<\/em> course from FastAI: Practical Deep Learning for Coders<\/a>. I actually stumbled across it via a video on YouTube, which I’ve watched now, and it made me feel optimistic about the course. I’m in the middle of the CS50 AI course<\/a> from Harvard, though, so I need to hold off on the FastAI course for now.<\/p>\n\n\n\n

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Above: Screenshot from FastAi course<\/em><\/figcaption><\/figure><\/div>\n\n\n\n

The first video got me thinking. <\/p>\n\n\n\n

First, they said (as many others have said) that Python<\/strong> is the main programming language used for machine learning today. (This makes me happy, as I know Python.) But I wonder whether there’s more to this claim than I’m aware of.<\/p>\n\n\n\n

Second, they said PyTorch<\/a> has superseded TensorFlow<\/a> as the framework of choice<\/em> for machine learning. They said PyTorch is “much easier to use and much more useful for researchers.”<\/p>\n\n\n\n

“Within the last 12 months, the percentage of papers at major conferences that use PyTorch has gone from 20 percent to 80 percent and vice versa \u2014 those that use TensorFlow have gone from 80 percent to 20 percent.”<\/p>\u2014Jeremy Howard, in the FastAI video “Lesson 1 – Deep Learning for Coders (2020)”<\/cite><\/blockquote>\n\n\n\n

Note, I don’t know<\/em> if this is true. But it caught my attention.<\/p>\n\n\n\n

FastAI <\/strong>is a library “that sits on top of PyTorch,” they explain. They say it is “the most popular higher-level API for PyTorch,” and it removes a lot of the struggle necessary to get started with PyTorch.<\/p>\n\n\n\n

This leads me back to the CS50 AI course. The CS50<\/strong> phenomenon was documented in The New Yorker<\/em> in July 2020<\/a>. One insanely popular course, Introduction to Computer Science, has spawned multiple follow-on courses, including the seven-module course about the principles of artificial intelligence in which I am currently enrolled (not for credit).<\/p>\n\n\n\n

In the various online forums and Facebook groups devoted to CS50, you can see a lot of people asking whether they need to take the intro course prior to<\/em> starting the AI course. Some of them admit they have never programmed before. They know nothing about coding. But they think they might take an AI programming course as their very first computer science course.<\/p>\n\n\n\n

This is what I was thinking about as the speakers in the FastAI video both<\/em> praised how easy FastAI makes it to train a model and<\/em> cautioned that machine learning is not a task for code newbies.<\/p>\n\n\n\n

Training and testing a machine learning system \u2014 a system that will make predictions<\/em> to be used<\/em> in some industry, some social context, where human lives<\/em> might be affected \u2014 should not be dependent on someone who learned how to do it in one online course.<\/p>\n\n\n\n

Some other free online courses:<\/p>\n\n\n\n