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emiruz.com | ||
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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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juliasilge.com
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| | | | | A data science blog | |
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svmiller.com
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| | | | | This is a basic tutorial for estimating the Poisson model, what it does, and how you should interpret what it tells you. | |
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www.integralist.co.uk
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| | | Introduction Information vs Data Frequency Watch out for misleading data Pie Chart Bar Chart Stacked Bars Split Bars Histograms Differences? Calculating dimensions Frequency Density? Line Graphs Averages Which average to use? Ranges Percentiles Variance Conclusion Introduction I started learning about statistics because I found myself doing a lot of operational monitoring (i.e. making systems more observable, instrumenting individual services, and monitoring that data via custom built dashboards). Althou... | ||
