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 ...

Get started with Machine Learning with Python - An introduction with Python programming examples - ml-MachineLearningWithPython/03 - Lesson - Linear Regression.ipynb at main · ...

"Name: House unit price, Length: 414, dtype: float64" ...

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 ...

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 ...

Abstract: The activation functions play increasingly important roles in deep convolutional neural networks. The traditional activation functions have some problems such as gradient disappearance, ...