Last Updated on June 7, 2016
There are a lot of blogs and videos on machine learning and more being created every day, week and month.
If you are working or at school, it can feel overwhelming to keep up with some much material. Worse, you feel like you will be at some great disadvantage if you do miss something.
In this post you will learn how subscribing to machine learning and data science newsletters can save you time and keep you up-to-date. You will also discover the 3 newsletters I recommend.
What You Will Learn
An approach that I use to keep abreast of good and interesting content on machine learning and data science is to subscribe to a newsletters. Newsletters arrive once per week or per month and summarize the best content on a topic for that interval.
The great thing about subscribing to newsletters, is that you no longer have to dip into news sites, twitter and blogs every day, you can wait until the best content for the week is delivered to you.
To ensure that you don’t miss a key piece of content, you can subscribe to a few different newsletters, each with a different perspective on the industry.
I have used this approach for years and highly recommend it. It saves time because you are not checking social news all day long, and you only read the best content, because someone else has filtered it for you.
Below are the 3 newsletters to which I subscribe. Take a look at each, and see if one or more are right for you.
Data Science Weekly
The Data Science Weekly newsletter has been running for nearly a year and is operated by by Hannah Brooks and Sebastian Gutierrez.
It is perhaps my favorite. It has a blog, interviews with data scientists, and a resource section. Check out the archive for past issues. You can see they have editor picks, top articles, books, training resources, book of the week.
The KDnuggest Newsletter is operated by Gregory Piatetsky, this newsletter has a mix of industry and academic news.
I like it for its focus on content, although there is a lot of content. This twice monthly newsletter that has a feature section, options and interviews, software, jobs, publications and more. It’s pretty focused around Gregory’s ecosystem, but I always find something interesting.
O’Reilly Data Today
The O’Reilly Data Newsletter is great, although I think of this as the Strata newsletter. It’s weekly and well put together.
It pushes the O’Reilly conference and books pretty hard, but gives a nice round up of the weeks news. Plus, when I’ve had my own content featured in there, it is brought my server down – it’s a beast. I think they do a better job of picking the big stories for the week and I’m always careful to read it through.
I run my own newsletter, but it provides tips and tricks for self-studying machine learning, rather than current news.
Some other resources for AI and data science news letters include:
- Daily AI Feed: I run my own AI newsletter called Daily AI Feed. It has a blog of past issues and still comes out every single day. I don’t think it’s very good anymore. It used to use a sophisticated algorithm to rank news articles and make picks, but it all fell to bits. Now it uses a white list of good blogs. It has seen better days, but there are still many hundreds of subscribers on there and they enjoy it.
- 10 Data Science Newsletters To Subscribe To: A list of 10 data science newsletters prepared by Berkeley School of Information. A weak list, lots of big data, spam and dead newsletters (although 2 of my picks are on it). The Data Science Central Newsletter looks OK.
If you subscribe to a machine learning newsletter, I’d love to here which one and what you think of it.
About Jason Brownlee
Jason Brownlee, PhD is a machine learning specialist who teaches developers how to get results with modern machine learning methods via hands-on tutorials.