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Some very useful materials from Data Science Central are provided by Ties de Kok. (Live links are in the attached pdf below)
This article provides a quick overview of the various types of NLP machine learning. Might be insightful if one wants to get a better understanding of the various options that are out there when it comes to classifying text documents.
This article describes the core steps of training a machine learning algorithm using the "sklearn" Python package which is arguably the most popular ML package out there. It is not very comprehensive but it is a good first read.
The question "which language should I use" tends to come up quite frequently, this article discusses this question from the perspective of machine learning. This is obviously not a black-and-white choice but at least it provides some discussion.
There are many different machine learning algorithms out there, so it might be a bit difficult sometimes to grasp the intuition of each of them. This article does quite a good job explaining the most popular algorithms.
Sometimes you need to run code that requires a more powerful system, or that requires longer run-times. For people that don't have access to remote computing facilities it might be an interesting option to use Google Colaboratory as a free alternative. This article explains what it is and how you can use it.
The website reports useful information about machine learning. Ties has picked some selected articles for your perusal.