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gregorygundersen.com | ||
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fa.bianp.net
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| | | | | MathJax.Hub.Config({ extensions: ["tex2jax.js"], jax: ["input/TeX", "output/HTML-CSS"], tex2jax: { inlineMath: [ ['$','$'], ["\\(","\\)"] ], displayMath: [ ['$$','$$'], ["\\[","\\]"] ], processEscapes: true }, TeX: { equationNumbers: { autoNumber: "AMS" }, extensions: ["AMSmath.js", "AMSsymbols.js"] }, "HTML-CSS": { fonts: ["TeX"] } }); In this post I compar several implementations of Logistic Regression. The task was to implement a Logistic Regression model using standard optimization ... | |
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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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www.ericekholm.com
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| | | | | Learning maximum likelihood estimation by fitting logistic regression 'by hand' (sort of) | |
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cyclostationary.blog
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| | | Our toolkit expands to include basic probability theory. | ||
