Creating a technical learning program can be time consuming and resource-intensive. Defining learning objectives, designing training materials, and gathering attendee feedback are just a few of the must-have's. Here is a quick, 10-step guide to help get your new program up and running successfully.
In this article, I discuss the difference between Featured Snippets and Rich Snippets and explain how Structured Data helps Google display your search engine listings. I also discuss why all three are good for SEO.
In Part 1, we explored some of the power offered by the pandas framework. Now we'll dive deeper into the tools such as grouping, aggregation, joins, advanced string methods and other functions.
Tired of your fellow humans being probed by aliens? It’s time to probe back! Well, at least, probe the data on UFO sightings. To do this, we’ll show-case one of the most popular open source tools for analyzing data: the pandas package.
Most working definitions of Big Data do not have an explicit reference to the size of the data set. This is because the associated conceptual, software, and hardware shifts derive from several important factors aside from actual size of the data.
We can apply machine learning to help detect credit card fraud, but there is a bit of a problem in that the vast majority of transactions are perfectly legitimate, which reduces a typical model’s sensitivity to fraud.
Whether you are fairly new to data science techniques or even a seasoned veteran, interpreting results from a machine learning algorithm can be a trying experience. The challenge is making sense of the output of a given model.
