Machine unlearning – a new frontier

machine unlearning

Since there is so much talk about machine learning and ways it could be utilized, it is time to mention the exact opposite of it. We have mentioned so many times that the ML model is only as good as the data it was trained on. But what happens when that data is no longer […]

Data poisoning – an unexpected foe

data poisoning

Recently, there has been a big buzz around the downsides and negative effects of AI and ML. This has sparked the conversation on adversarial ML and adversarial attacks. Alongside the usual types of attacks, one type has stood out, especially in consideration of copyright infringement. Data poisoning has been making waves, and now people are […]

From continuous intelligence to composite AI – a mix for success

continuous intelligence

Leveraging business intelligence to make decisions has been the core of any company that somehow wants to utilize data. An approach to the ever-growing data volume has been to integrate BI systems into everyday operations. Which is perfectly fine and might work for some. The issues appear when data velocity becomes greater and data starts […]

Utilizing multimodal ML in a fast-shifting world

multimodal ML

AI and machine learning are both terms that we so freely use. But, what many do not understand is that there are so many sub-areas of these disciplines. And we use them all interchangeably, which would be misleading. ML, in itself, can be divided into supervised, unsupervised, semi-supervised, and reinforcement learning. Each one comes with […]

What can we learn about federated learning?

federated learning

We all know that for machine learning you have to train models on data before actually having fully functional systems that derive results. The same goes for AI. The traditional approach is to collect data, prepare data, train models, and deploy them. But, considering the amount of data and devices we use daily, there was […]

Machine learning for mood prediction of high school students

machine learning

With recent developments in the field of machine learning, collecting and analyzing data has become a crucial part of improving almost every industry in the world. This is why researchers from the Faculty of Education and Rehabilitation Sciences in Zagreb approached us to determine to which degree state-of-the-art machine learning methods can predict the mood […]

The rise and impact of adversarial machine learning

adversarial machine learning

Getting into machine learning is all fine and well. And, yes, it’s something that has revolutionized businesses and started so many opportunities for better products and services. But, like with everything that brings good, there are threats to it. And in comes adversarial machine learning (AML), as a threat to machine learning and its outcomes. […]

Feature store in machine learning – why you need it?

feature store

With the way machine learning unfolds, data used in testing and modeling must come at the best quality relevant to the learning process. From data cleaning to data labeling, the process can be tasking. It’s not only about creating a simple data pipeline, machine learning and data processing extend beyond that. Machine learning often isn’t a […]

Synthetic data generation and why is it becoming popular

synthetic data

No one can stress enough how data is one of the most valuable resources these days, not only in business but in our daily lives as well. But like the real world, data also isn’t perfect. It’s hard and costly to collect data, and it comes with its own set of shortcomings, not to mention […]

Let’s dive into data science tools and algorithms

Data science tools

Croatia Osiguranje & BIRD Incubator Data Challenge – Part 2 After we explained fundamental data science concepts and techniques in the first part of this post, the second one will be about the tools and algorithms that were used during this Data Challenge. Data science tools As always, it is very important to use the […]