Blog Author: Danylo Pantielieiev

Trust is the cornerstone of AI adoption and acceleration. While healthy skepticism encourages rigorous development, trust in AI and its potential can lead to unprecedented advancements across industries. By fostering public understanding and implementing robust governance frameworks, we can build...

Statistic: Gartner forecasts that 85% of organizations will embrace a cloud-first principle by 2025.  Data platforms are essential tools for managing and analyzing large volumes of data. With the right platform, you can unlock valuable insights, drive informed decision-making, and gain a...

Neural networks have become cornerstone technology in AI, driving advancements in areas from image recognition to natural language processing. Traditional neural networks, however, have limitations, particularly in their ability to quantify uncertainty in predictions.  Bayesian Neural...

Machine learning pipelines automate and streamline the development, deployment, and maintenance of machine learning models. They ensure consistency, reduce manual effort, enhance scalability, and improve the reliability of your machine learning projects.  Ultimately, this automation...

Data leakage is a critical issue in machine learning that can severely compromise the accuracy and reliability of your models. It occurs when information from outside the training dataset inadvertently influences the model, leading to overly optimistic performance estimates.  Understanding...