Are you drowning in Data Lake?
Today more than even, every business is focusing on collecting the data and applying analytics to be competitive. Big Data Analytics has passed the hype stage and has bec...
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Data Science Simplified Part 8: Qualitative Variables in Regression Models
The last few blog posts of this series discussed regression models. Fernando has selected the best model. He has built a multivariate regression model. The model takes ...
Top Graphical Models Applications in Real World
1. Objective Now we are going to explain the various Graphical Models Applications in real life such as – Manufacturing, finance, Steel Production, Handwriting Recognit...
Machine Learning Vs. Statistics
This article was written by Aatash Shah. Many people have this doubt, what’s the difference between statistics and machine learning? Is there something like machine le...
Data Cleansing with Apache Spark and Optimus
Outdated, inaccurate, or duplicated data won’t drive optimal data driven solutions. When data is inaccurate, leads are harder to track and nurture, and insights may ...
Real-Life Applications of Support Vector Machines
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 number of appl...
When AI (Artificial Intelligence) Goes Wrong…
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 smarter than the hu...
Generative Adversarial Networks (GANs): Engine and Applications
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 generation fr...
Curious Mathematical Object: Hyperlogarithms
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) + Hlog(Y), wh...
Data Lineage: The History of your Data
Data Denialism A common scenario that data analysts in general encounter is what I like to describe as “data denialism”. Often, and especially while consultin...