Unless you’ve been living under that proverbial rock, you’ve at least heard of cryptocurrency – those digital, non-corporeal monetary units that have the world abuzz these days. Bitcoin is probably the most obvious such crypto coin, but there are plenty of others that have sprung up in the wake of bitcoin’s success, such as Ethereum and Ripple. However, chances are good that unless you’re a financial expert, and possibly even if you are such an expert, you’re not all that clear on what cryptocurrency is, how it works, the risks involved, or even why or how to accept it as payment. Within this guide, we’ll explore those topics and more to help you understand how to buy, use and invest with cryptocurrency. To many people, the term “cryptocurrency” might seem pretty self-explanatory, but if you take a deeper look at the subject, you’ll likely find that it’s more complicated than it might seem at first glance. After all, crypto coins have virtually nothing in common with traditional currency, other than acting as a store of value. Even that similarity can be questionable. So, what is a cryptocurrency?
Geospatial Big Data analytics are changing the way that businesses operate in many industries. Although a good number of research works have reported in the literature on geospatial data analytics and real-time data processing of large spatial data streams, only a few have addressed the full geospatial big data analytics project lifecycle and geospatial data science project lifecycle. Big data analysis differs from traditional data analysis primarily due to the volume, velocity and variety characteristics of the data being processed. One motivation in introducing a new framework is to address these big data analysis challenges. Geospatial data science projects differ from most traditional data analysis projects because they could be complex and in need of advanced technologies in comparison to the traditional data analysis projects. For this reason, it is essential to have a process to govern the project and ensure that the project participants are competent enough to carry on the process. To this end, this paper presents, new geospatial big data mining and machine learning framework for geospatial data acquisition, data fusion, data storing, managing, processing, analysing, visualising and modelling and evaluation. Having a good process for data analysis and clear guidelines for comprehensive analysis is always a plus point for any data science project. It also helps to predict required time and resources early in the process to get a clear idea of the business problem to be solved.
The hype about AI makes it difficult for experienced investors to understand where the real value and innovation in the technology are to be found. This paper helps to bring some clarity to what is happening on the investment side of the artificial intelligence industry.
The objective of this paper is to provide a comprehensive perspective on the advancements in the area of Artificial Intelligence and how the infusion of cognitive customer engagement can positively impact the infamously unpredictable consumer cyclical retail industry.