ADR Awareness Centre

Unlock the world of Geometric Learning and Graph Convolutional Networks (GCNs) in this comprehensive course designed to empower you with cutting-edge knowledge and practical skills.

Real-World Data Science Projects involve the practical application of data science methodologies to solve real-world problems.

There is an issue of domain shift in machine learning models, which occurs when models trained on one dataset perform poorly when tested on data from a different source.

An optimal recombination operator for two-parent solutions provides the best solution among those that take the value for each variable from one of the parents (gene transmission property).

After a brief introduction to image acquisition and light reflection, the building blocks of modern cameras will be surveyed, along with geometric camera modelling.

Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.