Posts

Abstract The prior distribution is the part of a Bayesian model that most often invites suspicion: “you can make a Bayesian analysis say whatever you want by twisting the prior.” That accusation is sharper than the textbook reply (“priors matter less than you fear, look at the posterior”) suggests, and it is sharper than the casual recipe (“just use a flat prior”) deserves. There are at least five inequivalent answers to “what does an uninformative prior even mean?”, the Jeffreys rule has a beautiful geometric derivation that is rarely spelled out, and improper priors can be perfectly safe or silently wrong depending on the dataset. ...

Abstruct With the development of modern data stacks, it is getting way easy to establish an useful data infrastructure. A lot of people spent much time to investigate and build them. However, as for dbt x aws, there are no resources on the internet. Therefore, I am going to give you a lecture about that. Goal I reckon that providing the results makes you understood more efficiently, so pasting some pictures. ...

Abstruct In this post, I am going to explain how mathematics is involved with Neural Network and how to implement it with only numpy. Content this post was written when I was a junior student. Therefore, there might be some mistakes. Please leave the comment below. Prerequisites rudimentary calculus knowledge Chain Rule Jacobi-Matrix This sections help you learn to take derivatives of vectors, matrices, and higher order tensors, thereby making you understand the following part. ...

Abstract I’ll show you how to allow markdown to display latex. This website uses hugo and it does not have the ability to render latex by default. $e^2$ In addition, I write down a way to solve a little latex problem. Content Setup First of all, create a file layouts/partials/extend_head.html with the following content. {{ if or .Params.math .Site.Params.math }} <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.15.2/dist/katex.min.css" integrity="sha384-MlJdn/WNKDGXveldHDdyRP1R4CTHr3FeuDNfhsLPYrq2t0UBkUdK2jyTnXPEK1NQ" crossorigin="anonymous"> <!-- The loading of KaTeX is deferred to speed up page rendering --> <script defer src="https://cdn.jsdelivr.net/npm/katex@0.15.2/dist/katex.min.js" integrity="sha384-VQ8d8WVFw0yHhCk5E8I86oOhv48xLpnDZx5T9GogA/Y84DcCKWXDmSDfn13bzFZY" crossorigin="anonymous"></script> <!-- To automatically render math in text elements, include the auto-render extension: --> <script defer src="https://cdn.jsdelivr.net/npm/katex@0.15.2/dist/contrib/auto-render.min.js" integrity="sha384-+XBljXPPiv+OzfbB3cVmLHf4hdUFHlWNZN5spNQ7rmHTXpd7WvJum6fIACpNNfIR" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script> <!-- for inline -->> <script> document.addEventListener("DOMContentLoaded", function() { renderMathInElement(document.body, { delimiters: [ {left: "$$", right: "$$", display: true}, {left: "$", right: "$", display: false} ] }); }); </script> {{ end }} Then, add the parameter in order to enable MathJax on config.yml as follows: ...