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...
Summary: How about a deep learning technique based on decision trees that outperforms CNNs and RNNs, runs on your ordinary desktop, and trains with relatively small dat...
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 ...
Data science is an interdisciplinary field of scientific processes, methods, and systems. It is used to extract insights from data in many forms, either structured or uns...
I’m reposting this blog (with updated graphics) because I still get many questions about the difference between Business Intelligence and Data Science. Hope this bl...
Another question recently posted on social networks. Below is my answer, with link to the original post. The main reason is the exponential growth of data science candi...
Organizations looking for justification to move beyond legacy reporting, should review this little ditty from the healthcare industry: The Institute of Medicine (IOM) est...