INTRODUCTION
Artificial intelligence is one of the fastest evolving science domains. It influences the route we take when we drive to work, how we use our phones and computers, what shopping we buy and what we will see in cinemas...
- Igor Zatoń
Thanks to science-fiction movies and books, the general public views AI as a creature that knows everything and can solve any problem better than we humans. In this vision, there is only one type of AI, which is General AI. Although work...
- Joanna Piwko
Image generated with Midjourney API, “Quantum Computing”
The blogs so far have been based on facts and knowledge backed by...
- Mateusz Papierz
Here goes a second edition of our special Christmas treat for you!
(The first one was about Santa Classification using classical Computer Vision techniques. It not only was accurate - catching even the Grinch - but also provided...
- Sylwana Kaźmierska
Application of Computer Vision in the Industrial Sector
Inventory management is a key process for all industrial companies, but the inventory process is both time-consuming and error-prone. Mistakes can be very costly, and it is highly...
- Igor Zatoń
Increasing yields has been a key goal for farmers since the dawn of agriculture. People have continually looked for ways to maximise food production from the land available to them. Until recently, land management techniques such as the use...
- Jim Carroll
When you want to take the best possible care of your brain, certain things are recommended, such as fatty fish, vegetables, doing some brain exercises, and learning new things. But what about artificial neural networks? Of course, they don’t...
- Joanna Piwko
Introduction
This is the first article in a series about Agile in the area of Data Science and Artificial Intelligence. It is necessary to explain the essentials first, before moving to more specific concepts. Especially that ...
- Daniel Rurarz
One very important part of working as a Data Scientist is often overlooked. I'm referring to the part which involves visualising data and results. You probably don't think that this is an exciting task, but let me explain why it is...
- Joanna Piwko
Data is all around us, and we don't even see it.
Data Scientists usually work on projects related to well known topics in Data Science and Machine Learning, for example, projects that rely on Computer Vision, Natural Language...
- Sylwana Kaźmierska
What are Generative Adversarial Networks?
A Generative Adversarial Network (GAN) is a concept that was developed in 2014 by a team of distinguished researchers led by Ian J. Goodfellow. In short, we train two deep neural networks in...
- Adam Gurgul
As humans, we have a visual system that allows us to see (extract and understand) shapes, colours and contours. So why do we see every image as a different image? How do we know, for example, that a box in an image is, in reality, a box? And...
- Adam Szummer
- Piotr Czembrowski
Autoencoders have existed in Data Science for a long time. This type of model has three sequential parts: the input layer (encoder); the hidden layer; and the output layer (decoder). It seems like a simple concept, but it is very powerful. You use...
- Joanna Piwko
Nowadays, no one needs to be convinced of the power and usefulness of deep neural networks. AI solutions based on neural networks have revolutionised almost every area of technology, business, medicine, science and military applications...
- Mateusz Papierz
In the previous article, I described attention mechanisms by using an example of natural language processing. This method was first used in language processing, but this is not its only usage. We can also use attention mechanisms in another...
- Joanna Piwko
For some reason, it is quite natural for people to argue with each other all the time. Wives argue with husbands. Children argue with their parents. Facebook users argue with other Facebook users. United fans argue with City fans. And it...
- Patryk Seweryn
According to some sources, over 40% of all Internet traffic is made up of bot traffic. And we know that malicious bots are a significant proportion of current bot traffic. This article describes a number of strategies (Machine Learning, user...
- Sylwana Kaźmierska
The attention mechanism made big changes in deep learning.
Thanks to this, models can achieve better results. This mechanism was also the inspiration for perceivers and also transformer neural networks . And transformers led to the...
- Joanna Piwko
Some say artificial intelligence (AI) will be the next big thing after the internet: a tool enabling new industries and improving the lives of ordinary people. Others think AI is the greatest threat to society as we know it. This article will try to...
- Tigran Soghbatyan
Review of Yoshua Bengio’s lecture at the Artificial General Intelligence 2021 Conference
At the 2021 Artificial General Intelligence Conference, a star keynote speaker was Yoshua Bengio. He has been one of the leading figures of deep learning with...
- Martin Kolar
The main focus in machine learning projects is to optimize metrics like accuracy, precision, recall, etc. We put effort into hyper-parameter tuning or designing good data pre-processing. What if these efforts don’t seem to work?
- Joanna Piwko
If I was to point out one most common mistake of a rookie Data Scientist, it’s their focus on the model, not on the data.
- Lukasz Kuncewicz
Since it’s 2021, it’s probably no surprise to you that heart rate can be measured using different gadgets like smartphones or smartwatches.
- Sylwana Kazmierska