Applications of SVM in Real World SVMs depends on supervised learning algorithms. The aim of using SVM is to correctly classify unseen data. SVMs have a… Read More »Real-Life Applications of Support Vector Machines
The intelligence in AI is computational intelligence, and a better word could be Automated Intelligence. But when it comes to good judgment, AI is not… Read More »When AI (Artificial Intelligence) Goes Wrong…
Generative adversarial networks (GANs) are a class of neural networks that are used in unsupervised machine learning. They help to solve such tasks as image… Read More »Generative Adversarial Networks (GANs): Engine and Applications
Logarithms turn a product of numbers into a sum of numbers: log(xy) = log(x) + log(y). Hyperlogarithms generalize the concept as follows: Hlog(XY) = Hlog(X)… Read More »Curious Mathematical Object: Hyperlogarithms
Data Denialism A common scenario that data analysts in general encounter is what I like to describe as “data denialism”. Often, and especially while consulting,… Read More »Data Lineage: The History of your Data
In the last few blog posts of this series, we discussed simple linear regression model. We discussed multivariate regression model and methods for selecting the… Read More »Data Science Simplified Part 7: Log-Log Regression Models
Agenda Introduction of Powershell Need of powershell BackGround of Powershell Tools Why its better than alternatives ? Top Most Administrative Powershell Commands Working with Pipeline… Read More »Windows Powershell Commands for Beginners
Top Neural Network Algorithms Learning of neural network takes place on the basis of a sample of the population under study. During the course of learning,… Read More »Neural Network Algorithms – Learn How To Train ANN
Summary: Recently we’ve been profiling Automated Machine Learning (AML) platforms, both of the professional variety, and particularly those proprietary one-click-to-model variety that are being pitched… Read More »More on Fully Automated Machine Learning
I describe here an interesting and intuitive clustering algorithm (that can be used for data reduction as well) offering several advantages, over traditional classifiers: More… Read More »Nice Generalization of the K-NN Clustering Algorithm — Also Useful for Data Reduction
