Overview This guide explores how intelligent systems can be structured using workflows (deterministic flows) and agents (autonomous decision-makers). Workflows ensure reproducible outcomes, while agents enable adaptability, reasoning, and context awareness in dynamic environments. Key Distinctions: Workflows: Predetermined logic and fixed ex... Read more 11 Nov 2025 - 3 minute read
Paper Deep Residual Learning for Image Recognition Authors: Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun ResNet ResNet short for Residual Network it tackled a major challenge faced by deep convolutional neural networks (CNNs) callws vanishing gradients. As CNNs grew deeper (more layers), training became increasi... Read more 04 May 2024 - 1 minute read
Paper Very Deep Convolutional Networks for Large-Scale Image Recognition Authors: Karen Simonyan, Andrew Zisserman VGGNet VGGNet are series of Convolutional Neural Network models proposed by the Visual Geometry Group of Oxford University, including the well known VGG11,VGG13,VGG16 and VGG19. Simplicity of Architecture: VGGNet’s arch... Read more 07 Apr 2024 - less than 1 minute read
Paper ImageNet Classification with Deep Convolutional Neural Networks Authors: Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton AlexNet AlexNet is a convolutional neural network that won the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2012. It was designed to recognize objects and faces from over a million differe... Read more 07 Apr 2024 - less than 1 minute read
Activation Functions: Purpose: Activation functions determine the output of a neural network node given an input or set of inputs, introducing non-linear properties to the network enabling them to learn complex patterns. Activation functions help decide whether a neuron should be activated or not, influencing the network’... Read more 27 Feb 2024 - 19 minute read