找到了一個比較好的隱馬爾可夫過程教程，我翻譯並記錄一下。

今天給大家介紹隱馬爾可夫模型是什麼，以及它是如何工作的， 並介紹它在資料科學方面的應用。

For those of you who have been here before, you know that previous meetups for the Tucson Data Science Group have primarily focused on deep learning, namely ANNs, and while it important to keep up with the cutting edge technology, HMMs are extremely vital to know because they have been around for a long time AND are still consistently used by researchers in many fields such as NLP and especially in bioinformatics.

By the end of this talk you should have a solid understanding of HMMs, how to use them, and what you can use them for.

I’ll review the general intuition behind Markov processes, Markov chains, the architecture and the algorithm of an HMM,

and then go through an example in Python

before discussing some of the contemporary work that is being done with HMMs as well as my own work in bioinformatics.