Beyond the Line: How Activation Functions Unlock Complex Learning in Neural Networks
Here are some of the most famous activation functions used in neural networks, along with their advantages and disadvantages: 1. Sigmoid Function: Output: Ranges between 0 and 1 (squashes the input values between 0 and 1). Advantages: Smooth output, making it suitable for modeling probabilities (often used in output layer for binary classification). Well-behaved gradients for backpropagation (a technique…
Dr. Amit is a seasoned IT leader with over two decades of international IT experience. He is a published researcher in Conversational AI and chatbot architectures (Springer & IJAET), with a PhD in Generative AI focused on human-like intelligent systems.
Amit believes there is vast potential for authentic expression within the tech industry. He enjoys sharing knowledge and coding, with interests spanning cutting-edge technologies, leadership, Agile Project Management, DevOps, Cloud Computing, Artificial Intelligence, and neural networks. He previously earned top honors in his MCA.
