Ask HN: What's the state of machine learning, and should new entrants pursue it?

6 pointssendos2 comments

What's the state of machine learning today, as a field? Have the "big problems" been solved (and only evolutionary tweaks remain), or are there major problems still to be solved?

The question is mainly related to whether it makes sense today for someone to go into this field, or is it too late for major contributions to be made?

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Andrew Ng's course on Machine Learning (https://www.coursera.org/course/ml) has rave reviews whenever I see it mentioned. It just started again a few weeks ago and I had hoped to join this time, but other commitments made that impossible.

As for the other part of your question...You may as well be asking if it's too late to research 'science'. Machine Learning may have been studied for a fair few years now, but it is still very much in its infancy. The possible developments in this area we can't yet imagine dwarfs the possible developments we can, which in turn dwarfs the 'major contributions' so far.

There's still plenty of new ground to be covered, have a look at conference proceedings to see what areas are currently hot.

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