The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression analysis. We will continue to use the ...

A linear function approximator is a function y=f(x,w) that is linear in the weights, though not necessarily linear in the input x: Linear function approximators have several nice properties. For ...

The linear function is popular in economics. It is attractive because it is simple and easy to handle mathematically. It has many important applications. Linear functions are those whose graph is a ...

Summary In this lesson, we learnt the basics of simple linear regression between two variables as a problem of fitting a straight line to best describe the data associations on a 2-dimensional plane.

In today's deep learning community, three activation functions are commonly used: the sigmoid function, the tanh function and the Rectified Linear Unit, or ReLU for short. When you're building a deep ...

Finding the slope of a linear function is straightforward. Furthermore the slope is the same at each point on the function. However this is not the case with non-linear functions. A non-linear ...

Abstract: Deep Learning is attracting much attention in object recognition and speech processing. A benefit of using the deep learning is that it provides automatic pre-training. Several proposed ...