Topics

Here you will find articles primarily about artificial intelligence: its uses, its underlying theory, practical implementations, and how it is changing the world.

What is it like to be a data scientist? What is needed beyond the technical skills? Learn how to break into your first data science role, how to advance in your career, and tips and tricks from those who have been there.

Computer vision (CV) is concerned with using computers to process and extract information from image and video. Read articles on a wide range of CV related concepts.

Data engineering encompasses the design, building, and implementation of systems for the collection, management, and analysis of data. Data science can't happen without data engineering.

Data science is the application of scientific tools for the extraction of insights from data. It's a very broad topic, and somewhat of a catch-all. If it isn't categorized elsewhere, you'll likely find it here.

From algorithm theory, to implementation, to the practical application of machine learning methods, you'll find technical articles, opinions, and tutorials here.

MLOps is the process of taking a machine learning model or system to production, and then monitoring and maintaining that system over time. A model can't be leveraged if it's not deployed, and so realizing the full potential of machine learning lies in MLOps.

Natural language processing (NLP) is concerned with the use of computers to process and extract insights from human language. Find a wide range of NLP related articles here.

Read news from KDnuggets (such as our top weekly posts) and from around the web here.

Programming is one of the most important technical tools at our disposal, and here you can find all sorts of articles for refining this skill.

There are lots of programming languages one can use for data-related programming, but Python has captured a special place in the hearts of many, including ours.

SQL is often described as the language of data, and as such it has a unique spot in data disciplines, and in our list of topics.