In our era, customers can easily hop from one brand to another, leaving companies little room for error. In this context, firms must strive to ensure exemplary customer experience at every interaction. Moreover, because business data is so readily available and competition so fierce, companies face immense pressure to streamline their operations or risk demise.
How do companies develop an understanding of how past action and behavior impact future outcomes? With the field of predictive analytics, it’s easier than ever for companies to anticipate customer expectations.
Doing so enables them to not only preserve the customer experience, but it also allows them to reduce costs, increase efficiency, and improve work conditions, among a myriad of other benefits. With that in mind, let’s take a closer look at predictive analytics.
The internet is overflowing with resources for learning new programming skills. For thriving disciplines like natural-language processing (NLP), you can find plenty of tutorials, video series, and university lectures online. All of these formats can be great ways to get you started. But when you want to get a truly deep understanding of a new topic, nothing beats a good book. For this article, we’ve compiled a list of our all-time favorite books that you should have in your pack before embarking on your NLP journey.
Are you obsessed with finding patterns in data? Do you want to learn more about data analysis and ways to break into this interesting line of work? If you answered yes to these questions, this article is a great place to start.
In this article, we’ll take a deep dive into the process of qualitative data analysis, learn what it is, how it works and some effective methods of analyzing data.
You’re admiring a sleek autonomous vehicle on the road, when suddenly you see a dog run into the intersection. The pup seems doomed, but the driverless car slows and stops just short of disaster. Given that no quick-thinking human’s hand was on the wheel, how was this accident averted?
Autonomous vehicles are the latest players in the ecosystem of sensor fusion, which combines sensors that track both stationary and moving objects in order to simulate human intelligence. As you might deduce from its name, the discipline fuses together the signals of multiple sensors to determine the position, trajectory, and the speed of an object.
Online learning has never been more important. COVID-19 closed schools and over 67% of students worldwide are unable to attend class on campus. And scores of businesses closed causing unemployment to rise to 10%.
Fortunately, with just a computer and internet access, you can learn just about anything — from anywhere — even tech skills.
In fact, there has never been a better time to add technological know-how to your resume. A recent report showed that the tech industry generated $1.9 trillion, or about 10% of the economy in the United States. The tech industry is huge, and only growing bigger.
Every day, billions of queries are entered into the Google search bar. We’re constantly looking for something — the definition of a word, the bus schedule, the lyrics to that certain song. However, in the realm of computer science the term “search” has a slightly broader meaning. With search algorithms, we’re often not looking for a single item, but for a series of steps: the optimal strategy for solving a given problem. That fact is what makes this family of algorithms so central to so many different applications.