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cyclostationary.blog | ||
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akosiorek.github.io
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| | | | | Machine learning is all about probability.To train a model, we typically tune its parameters to maximise the probability of the training dataset under the mo... | |
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tiao.io
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| | | | | One weird trick to make exact inference in Bayesian logistic regression tractable. | |
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www.jeremykun.com
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| | | | | Machine learning is broadly split into two camps, statistical learning and non-statistical learning. The latter we've started to get a good picture of on this blog; we approached Perceptrons, decision trees, and neural networks from a non-statistical perspective. And generally "statistical" learning is just that, a perspective. Data is phrased in terms of independent and dependent variables, and statistical techniques are leveraged against the data. In this post we'll focus on the simplest example of thi... | |
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teddykoker.com
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| | | In this post we will be using a method known as transfer learning in order to detect metastatic cancer in patches of images from digital pathology scans. | ||
