Machine learning is an application of artificial intelligence that gives a system an ability to automatically learn and improve from experiences without being explicitly ...
In the last blog post of this series, we discussed classifiers. The categories of classifiers and how they are evaluated were discussed. We have also discussed regressi...
Sometimes a recruiter will find difficult to know the skills of a data science before hiring. Here are some simple questions to measure the ability of a data science: 1) ...
Even those new to IT have probably heard that everyone is “moving to the cloud.” This transition from standard infrastructure is thanks in large part to Amazon Web Se...
Spark VS Hadoop Spark and Hadoop are two different frameworks, which have similarities and differences. Also, both of them have their unique pros and cons. So, which one...
Time series forecasting is hardly a new problem in data science and statistics. The term is self-explanatory and has been on business analysts’ agenda for decades now: ...
This article is inspired by this SIGGRAPH paper by Levin et. al, for which they took this patent , the paper was referred to in the course CS1114 from Cornell. Thi...
In this article, interactive image segmentation with graph-cut is going to be discussed. and it will be used to segment the source object from the background in an im...
I was recently asked to conduct a 2-hour workshop for the State of California Senior Legislators on the topic of “Big Data, Artificial Intelligence and Privacy.” Hono...
When it comes to Data Science, the most recurring topic is modeling. Quite a few articles out there talk about data preparation and only a bunch about how to communicate ...