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Learning about machine learning

Tuesday, 15 March, 2016

On Friday, here, we watched Stephen Wolfram speak about the next language. What it’s going to be is undefined, but if we want computers to do increasingly complex things, a shared language will be required. This “code” will express our needs, our wishes, in a way machines can understand. Wolfram’s profound belief is that coding for this future has a philosophical, humanistic, perhaps, divine, purpose. Most people, however, see it in a more prosaic light: learning about the “soul of the machine” is about getting a job.

Enrollment in machine learning classes is soaring in the US, and universities are scrambling to add classes to meet an unprecedented demand writes Jamie Beckett in an NVIDIA blog post. At Carnegie Mellon University’s Machine Learning Department, enrollment in ‘Introduction to Machine Learning’ has jumped nearly 600 percent in the past five years. Applicants to its machine learning Ph.D. program have doubled in six years and the university has added its first undergraduate course on the topic. At the University of California, Berkeley, enrollment in ‘Introduction to Machine Learning,’ has nearly tripled in less than two years says Beckett.

Quote: “In the old days, you had to take an introductory computer class so you’d know how to use a computer at work,” said Lynne E. Parker, division director for the Information and Intelligent Systems Division at the National Science Foundation. “Today, students are recognizing that whatever their chosen field, there’s going to be some automation of the knowledge work — and that’s machine learning.”

Note: Coursera is offering Machine Learning Foundations: A Case Study Approach.

machine learning

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