The best Machine Learning blogs
A list of the best blogs about Data Science and Machine Learning
In this section you will find the best blogs about Machine Learning and Data Science, along with a brief description of what their purpose is, their technical level, and what you will find in them. Keep tuned, as these blogs are updated regularly to bring you the best fresh content!
Enjoy this fantastic list of resources we have put together for you.
KDNuggets is one of the most well known Machine Learning and Data Science blogs out there. It is continuously posting articles about all sorts of topics related to these fields: from easy hands-on explanation of algorithms, to complex projects or advice.
It contains a section with where to find many datasets, and a section about Artificial Intelligence related jobs and PhDs, so be sure to take a look!
Machine Learning mastery is another great blog for learning Machine Learning. Led by PhD Jason Brownlee, this blog is oriented towards helping developers and Machine Learning practitioners better understand the field, and accelerate their work.
Almost every article explains theoretical concepts using code examples, so that you can instantly see a practical application of what is being explained.
Machine Learning plus is similar to the previous blog, but even more programming oriented. While Machine Learning mastery provides and depth explanation with complementary code, Machine Learning plus centres the learning on the code, and surrounds it with theory about our favourite Machine Learning notions: PCA, different algorithms, Data Manipulation.
It has code examples both on R and Python, as long with Python Programming 101 and tutorials of the most used libraries for Data Analysis: Pandas, Numpy, Matplotlib, etc…
Machine Learning from scratch is an awesome blog for practitioners, because it includes complex projects, focusing on how to implement them from end to end, which goes a little bit further than the normal theory with code tutorials we can find elsewhere.
It is not the best place to learn from zero, but if you have certain knowledge of the field of Artificial Intelligence and computer science you will enjoy this blog a lot. It has three main categories: Deep Learning, Machine Learning and Maths for ML, and a Medium-like feel that makes it very nice and easy to read.
Data Science Central is one of the best blogs about Data Science out there. From Statistics to Analytics to Machine Learning to AI, Data Science Central provides a community experience that includes a rich editorial platform, social interaction, forum-based support, plus the latest information on technology, tools, trends, and careers.
Data Science Central also offers webinars and a unique membership package that provides access to everything on the site for free. It has a forum and is a great resource for discussion, complex problem solving and research of different topics, although it is not the place you should head to if you are just starting.
Towards Data Science is one of the largest Medium publications, dedicated to divulging Data Science, Artificial Intelligence and Machine Learning knowledge. In it you can find all kinds of articles: from simple 101 Tutorials about Models, algorithms and concepts, to explanations of scientific papers or complete end to end projects.
Elite Data Science is a blog that is mainly oriented to guiding those who want to build a career in Data Science. It does not have the outstanding amount of theoretical articles that other blogs accumulate.
Instead, it orients future professionals towards the most essential knowledge and the industry de-facto tools for becoming a professional Data Scientist. You will directly be directed in the direction of real-world business value machine learning.
Revolutions is a blog dedicated to news and information of interest to members of the R community. This blog focuses on the latest news about AI, Machine Learning and Data Science, and is frequently updated. It is mostly oriented towards R users, but practitioners of other languages like Python can enjoy its contents too.
Peter Warden is an engineer, author of The Public Data Handbook and The Big Data Glossary for O’Reilly, builder of OpenHeatMap and the Data Science Toolkit, and other open-source projects.
His blog has amazing well-structured short articles that are informative and didactic, however, it is not a blog for beginners. The blog has no subsections, it is just a list of articles that are very interesting but that might escape out of the reach of those that are starting to learn about Data Science. Definitely a place for people with knowledge to devour, but not a resource to learn from scratch.
Microsoft’s Machine Learning blog is a resource that can serve many purposes. Structured as a simple list of articles ordered by date it contains from posts about how Machine Learning can improve business, where no tech background is needed, to articles about Deep Learning.
Most of the posts however, are oriented in the first manner: How can the field of Artificial Intelligence impact or improve specific scenarios, how or why implement Machine Learning in an organisation, and lots more.
QuantDare is a blog run by an Spanish Artificial Intelligence company, ETS Asset Manadgement , dedicated to advising investors on their movements and portfolios using AI.
It has a ton of fantastic articles that explain topics such as Bagging and Boosting, autoencoders, and Generative Adversarial Networks (GANs) using very clear examples and great graphic content. They also have specific content related to asset management or risk management using Machine Learning both in Python and R. Check it out, because it is a gem!
Algorithmia is a company that provides a framework for deploying Machine Learning models. This is one of the most overlooked parts of Machine Learning: everybody focuses on studying the theory of the algorithms and getting great AUCs or accuracies, without ever bothering where the developed systems are going to be used, or how to provide real value with them.
For this to happen, the implemented algorithms have to be deployed and an infrastructure has to be created and maintained. Algorithmia’s blog speaks just about this: how to handle the life-cycle of a Machine Learning product and how to deploy it.
Google’s Artificial Intelligence blog is a very good resource for those who have an ongoing career on Artificial Intelligence and want to stay up to date with the newest advances.
On it, they publish articles about the latest news on the field, in a paper-like manner, which makes it hard to approach for people without a thorough understanding of Artificial Intelligence and Machine Learning. However, for those with some degree of expertise, this resources is gold.
How to learn Machine learning is not a normal kind of AI blog. Articles here are published frequently, but the main purpose of the web-page is to be a repository, a place where people willing to learn Machine Learning or to expand their knowledge can go to, not just to read top-quality articles, but also to find top-quality, analysed, and reviewed resources that they can use to kick-start or upgrade their level of learning. Definitely one of the best Machine learning blogs.
Thank you very much for browsing through our Machine Learning blogs category. We hope that you found enough websites and Data Science blogs to have unlimited quality reading material to learn from. Best of luck!