Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Neuron a

The video tutorial explains the concept of neurons as computational units in the brain, describing the biological neuron model and its functions. It explores the ongoing research into neuron computation and introduces the perceptron model, highlighting its components such as inputs and weights. The tutorial discusses activation functions, including the step function, and their role in neural networks. Finally, it explains neural network learning, focusing on weight optimization for accurate data classification.

How do inputs and weights contribute to the output of a neuron?

What challenges are associated with using step functions as activation functions?

What are the parameters of a neural network model that need to be learned?

What is the difference between classification and regression problems in the context of neural networks?