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blog.cy.md | ||
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michael-lewis.com
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| | | | | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background. | |
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algobeans.com
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| | | | | Modern smartphone apps allow you to recognize handwriting and convert them into typed words. We look at how we can train our own neural network algorithm to do this. | |
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thenumb.at
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www.paepper.com
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| | | When you have a big data set and a complicated machine learning problem, chances are that training your model takes a couple of days even on a modern GPU. However, it is well-known that the cycle of having a new idea, implementing it and then verifying it should be as quick as possible. This is to ensure that you can efficiently test out new ideas. If you need to wait for a whole week for your training run, this becomes very inefficient. | ||
