I gained my first experience in the field of Artificial Intelligence during my master studies in multiple courses delving into the intricacies of Adversarial Attacks during the pursuit of my master’s thesis. It demonstrated to me the complexity of creating robust and resilient models. While I got even more excited for the technology, this experience protected me from being too optimistic on how fast we can create actual products from low-cost small R&D projects. There is no fast track for this, just a difficult but learnable (and hence entertaining) one.

My journey after graduating has led me to confront a myriad of challenging AI tasks, both supervised and unsupervised, as I strive to push the boundaries of what is achievable. From image classification and audio processing to anomaly detection and beyond, each task presents an opportunity to harness the true potential of AI.

Well, we all have heard of AI pretty much in the recent month and I am pretty sure we will hear even more in the years to come. After some time I have heard of so many sub-domains in the field of AI (too many to cover them all dilligentle) but a few in particular I could embedd in my free time. I invite you to join me on some hands-on AI project (mostly related to my robotics tasks). AI While all articles will be known for many AI enthusiasts frequently reading on medium.com, towardsdatascience.com or machinelearningmastery.com they are not less cool, are they not? 🙂

Predictive Analysis

Introduction: In the ever-evolving landscape of data-driven decision-making, one concept stands out as a guiding beacon – Predictive Analysis. It's not just a tool; it's a crystal ball that allows us to peer into the future, unraveling patterns, a...

Reinforcement Learning

Introduction: In the vast landscape of artificial intelligence (AI), there exists a paradigm that mirrors the way humans learn through trial and error – Reinforcement Learning (RL). Much like training a skilled athlete or guiding a curious child, R...