When in 2019 I started this blog, I allowed myself to be a little controversial by writing "AI will change the world more than the industrial revolution." Of course, prediction is very difficult, especially if it's about the future (Niels Bohr), but recent developments in machine learning have made me...
In machine learning designing the structure of the model and training the neural network are relatively small elements of a longer chain of activities. We usually start with understanding business requirements, collecting and curating data, dividing it into training, validation and test subsets, and finally serving data to the model....
Preparing your data for machine learning is not a task that most AI professionals miss. Data are of different quality, most often they require very thorough analysis, sometimes manual review, and certainly selection and initial preprocessing. In the case of classification tasks, the division of a dataset into classes may...
Computer Vision is one of the most interesting and my favorite application area for artificial intelligence. A big challenge for image analysis algorithms is fast detection and classification of objects in real time. The problem of detecting objects is much more difficult than the classification that I have discussed many...
Looking at the advances in technology over the past few years, it's hard to name two more breakthrough technologies than artificial intelligence and blockchain. The former opened up entirely new possibilities in the fields of data analysis, predictions and robotics. The later one elevated decentralization, transparency and security as a...
Until recently, a large part of the key concepts in the field of artificial intelligence was not so clearly defined. Some of them, such as Deep Learning, were even referred to as "buzzwords", term used mainly by marketing and not strictly translated into scientific areas. Now, the basic concepts seem...
