Data Science & Developer Roadmaps with Chat & Free Learning Resources
Non-Linear Models
When the formula looks nice but is hurting the analysis This is not my first blog concerning non-linear models. In fact, if you sift through my lists of blogs, you can see I applied quite a couple of...
Read more at Towards AI | Find similar documentsPyTorch Introduction — Enter NonLinear Functions
Pytorch Introduction — Enter NonLinear Functions Continuing the Pytorch series, in this post we’ll learn about how non-linearities help solve complex problems in the context of neural networks Neural...
Read more at Towards Data Science | Find similar documentsSimulating data from a non-linear function by specifying a handful of points
Trying to simulate data with non-linear relationships can be frustrating, since there is not always an obvious mathematical expression that will give you the shape you are looking for. I’ve come up wi...
Read more at R-bloggers | Find similar documentsExplicit feature maps for non-linear kernel functions
How to generate and compact feature representation for non-linear kernels with applications to supervised and unsupervised machine learning problems.
Read more at Towards Data Science | Find similar documentsNonlinear Regression Tutorial with Radial Basis Functions
Let's take a look at basis function regression which allows us to model non-linear relationships. If you are familiar with regular linear regression, then you know the goal is to find parameters…
Read more at Analytics Vidhya | Find similar documentsNon-linear SVM
Non-linear SVM Perform binary classification using non-linear SVC with RBF kernel. The target to predict is a XOR of the inputs. The color map illustrates the decision function learned by the SVC.
Read more at Scikit-learn Examples | Find similar documentsACTIVATION FUNCTIONS
Activation functions are the equations that determine the output of a neural network. The main purpose of an activation function is to introduce non-linearity to the neural network.
Read more at Analytics Vidhya | Find similar documentsActivation Functions in Neural Networks
As you can see the function is a line or linear. Therefore, the output of the functions will not be confined between any range. It doesn’t help with the complexity or various parameters of usual data…...
Read more at Towards Data Science | Find similar documentsNon-linear regression: basis expansion, polynomials & splines
Non-linear modelling with piecewise polynomials, cubic splines, natural splines and smoothing splines.
Read more at Towards Data Science | Find similar documentsClassical Neural Net: Why/Which Activations Functions ?
Activation functions are a family of functions that holds the purpose of introducing non-linearity after a layer computation. Indeed without an activation function no matter how much augmentation or…
Read more at Towards Data Science | Find similar documentsModeling Non-Linear Dynamic Systems with Neural Networks
In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers…
Read more at Towards Data Science | Find similar documentsFunctions
Functions are a set of instructions that return one value. Functions that exist in an object are typically called methods. Function Basics A function is declared using the def keyword. We close a func...
Read more at Codecademy | Find similar documents- «
- ‹
- …