Stochastic Gradient Descent.

Stochastic Gradient Descent (SGD) The stochastic method referred to is Stochastic Gradient Descent (SGD). Unlike traditional gradient descent, which uses the entire dataset to compute the gradient of the loss function, SGD updates the model parameters using only a...

Turing Proposes his Test for thinking

The Turing Test, proposed by Alan Turing in 1950, is a seminal concept in the field of artificial intelligence that aims to answer the question, “Can machines think?” Instead of attempting to define “thinking” in abstract terms, Turing devised...

Intelligent Machinery

Alan Turing, in his exploration of artificial intelligence and machine learning, introduced the concept of a system that operates based on principles similar to the “Law of Effect,” which he referred to as the “pleasure-pain system.” This...

Gradient descent technique

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for finding a local minimum of a differentiable multivariate function. The core idea behind gradient descent is to iteratively adjust the parameters of...