Deep Learning

Prompt engineering is a vital part of generative AI. Learn about the various prompt engineering techniques and their benefits.

Graph Neural Networks (GNNs) operate on graph-structured data, enabling them to learn relationships and patterns within complex networks.

DETR is a method for object detection with transformers. Explore its architecture, how it predicts bounding boxes and labels, and use cases.

Is AGI already here? We discuss everything you need to know about the 3 types of artificial intelligence in a complete guide.

Why did your model give that output? Learn how explainable ai gives insight into model decisions for trust and accountability in ML systems.

With the arrival of ChatGPT, AI content is everywhere. Learn about methods and tools to spot different types of AI-generated content.

Everything you need to know about the ImageNet dataset and its resounding impact on the world of computer vision and machine learning.

Our guide to Detectron2 dives into the framework’s computer vision capabilities, covering everything from its architecture to use cases.

We deep dive into the foundations of deep learning with deep belief networks: their architecture, capabilities, applications and challenges.