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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...

In the previous three parts of the tutorial, we learned about convolutional networks in detail. We looked at the convolution operation, the convolutional network architecture, and the problem of overfitting. In the classification of the CIFAR-10 dataset we achieved 81% on the test set. To go further we would have...

Deep neural networks are widely used in image and shape recognition. Examples of applications include face recognition, image analysis in medicine, handwriting classification, and detection of surrounding objects. A special type of neural network that handles image processing extremely well is a convolutional neural network. I have to admit that ConvNet...

Shape recognition, and handwritten digit recognition in particular, is one of the most graceful topics for anyone starting to learn AI. There are several reasons, but the two most important are the ease with which we can use well-prepared ready-made datasets and the ability to visualize these data. From this...