Machine learning is an ever-increasing world, and information gathering is indispensable. You can read blogs and news articles, follow people tweeting about machine learning on Twitter, and check the papers on arXiv every day. I think that we are collecting information by such a method.
The problem when collecting information is that there is too much information and important information is buried. The usual solution to this problem is to read articles with a lot of likes and bookmarks, narrow down the people you follow, or use some curation tool.
One of the recommended methods for those who want to check important information efficiently is to subscribe to the e-mail newsletter. Some of the benefits of subscribing to a machine learning e-mail newsletter are:
(↓ Usually delivered like this)
In this article, we will introduce 14 e-mail newsletters that are useful for gathering information on machine learning.
Here are 14 e-mail newsletters that are useful for gathering information on machine learning. It won't be too long to introduce one by one, but it often includes a combination of four main weekly news items, commentary articles, machine learning projects, and dissertations.
In most e-mail newsletters, you can see the contents delivered in the past on the Web, so it is better to see it once before deciding whether or not to subscribe. Below are 11 machine learning e-mail newsletters: (I personally like the ones in bold)
Weekly Machine Learning and Weekly Kaggle News are available in Japanese.
The following three are Python e-mail newsletters. Python is often used in machine learning, so it's helpful to subscribe:
If you know of other sites and methods that say "This is good!", Please let us know in the comments.
Machine learning is an ever-increasing world, and information gathering is indispensable. In this article, we have introduced an e-mail newsletter for efficient and effective information gathering. By the way, after sorting the delivered emails with a mailer, I put interesting articles in Pocket and read them slowly over the weekend. We hope you find this article useful.
I also tweet information about machine learning and natural language processing on my Twitter account. @Hironsan
We look forward to your follow-up if you are interested in this area.
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