AI & Machine Learning

Talent mobility is one of the best practices any company can incorporate into their activities as it is sure to give them very good results in terms of growth and overall development of such a company

Here are 8 Machine Learning tips that will help you to train a model with fewer screw-ups. These tips are most useful when you need to construct the training set.

Here are the opinions of prominent researchers in the field of graph ML and its applications trying to summarise the highlights of the past year and predict what is in store for 2021.

Here are 10 things about learning data science useful in getting you started on your data science journey or if you have already started, hope that you can find something useful from it.

In 2021, AI will become even more commonplace, and with this, the AI divide will grow more ubiquitous. Although AI tools are being applied in nearly all industries to a greater or lesser extent, here are the domains that will stand out in terms of putting AI to use in their operations on a global scale.

In the next ten years, computer vision will make huge strides. This article shows the trends and breakthroughs of the 2010s and what we can expect as we enter the 2020s.

Focus on research in Artificial Intelligence (AI) is nowadays growing more and more every year, particularly in fields such as Deep Learning, Reinforcement Learning and Natural Language Processing

Interest continues to grow in Enterprise Knowledge Graph (EKG). Graph Databases still outpace interest growth of all other database types by a wide margin.

There seems to be little consensus on what real-time ML means, and there has not been a lot of in-depth discussion on how it is done in the industry. This post shares two levels of real-time machine learning for online predictions, and online learning.

Underspecification facing machine learning is relatively new, and very important. How to solve it is an important question not only to the practical problem of making model deployment more stable, but how to make models actually learn the mechanics of the data instead of taking shortcuts or generating nonsense artificial solutions.

Here is a map of Artificial Intelligence (2020). This map is not a precise reflection of the state of the AI field, but just subjective representation. It contains more than 200 words or phrases, so to describe all of them would be too extensive and overkill.