Some original and very interesting material is presented here, with possible applications in Fintech. No need for a PhD in math to understand this article: I tried to make the presentation as simple as possible, focusing on high-level results rather than technicalities. Yet, professional statisticians and mathematicians, even academic researchers, will find some deep and fascinating results worth further exploring. Source code and Excel spreadsheets are provided for replication…

Which statistical method you use to compare data sets depends on two main factors: your overall goal and the type of data you have. Parametric data means that you know the underlying distribution (for example, your data might be normally distributed).…

In the early 2000’s, IBM Deep Blue was on the lookout for its next Grand Challenge.  It had achieved an exhilarating win over chess grand master Garry Kasparov in 1997.  But that was a game with deterministic outcomes where superior processing power gave Deep Blue a significant advantage over even a human grand champion.  IBM needed a challenge commiserate with its Artificial Intelligence aspirations, and the wildly popular TV game show…

Originally posted by Zeeshan Usmani in May 2015.

Big Data, Data Sciences, and Predictive Analytics are the talk of the town and it doesn’t matter which town you are referring to, it’s everywhere, from the White House hiring DJ…

The process of software development is rapidly evolving with the emerging new technologies being introduced in the field. In order for any software development service to be reliable and successful, it is necessary for the software development team to keep up with these technologies.

Some of the latest tech trends influencing the field…

Why Data Scientists Should Be Using LinkedIn

To date, there are more than 830,000 data science LinkedIn profiles registered worldwide. Despite this number of Data Scientists available/in roles online currently, it’s no secret there is still a major talent shortage. In fact,…

In a modern world of advanced technologies, our life is literally impossible without cellular telecommunications. Today, smartphones and wireless broadband Internet are common things for everybody. And recently, all developments and innovations in cellular technology are not about the availability of mobile connectivity but about bringing it to a…

Here is our list of featured articles and technical resources posted since Monday:

Announcement:

• Scaled for your Workload. Configure your Machine Learning Server. GPU-accelerated power and performance to deliver the most efficient, comprehensive solution, from processing massive datasets for scientific visualization and simulation to final batch rendering in the data…

Here is a short blog I was asked to make about making a personal Wiki from Wikipedia. It shows the basic steps in text processing so I hope it will be useful for data scientists. It also requires some knowledge of MediaWiki setup on a web server, and some (not very advanced) knowledge of the Python programming language. It takes only several days to create this Wiki with Wikipedia articles if you know…

As the world continues to collect more and more data with every passing second, it is only understandable that we would need tools that would help us make sense of all the data at our disposal. There are undoubtedly a variety of potent tools that are capable of doing just that; big data has managed to stand out from the crowd. Why? Primarily because it brings with it the promise of just the kind of insights and intelligence businesses need to not only improve their ability to gauge precisely…

Problem detected

What factors contributed to the economic crisis in the United States of America?

The question above is actually also being asked by the people there (USA), and even the world community. With the value of each proportion (in percentage).

There are several things that need to be underlined, including:

1. it is known, that financial factors have contributed 18% or the largest of the 7 factors + others.
2. but, when viewed from consumer…

Cybersecurity Data Science (CSDS) is a rapidly emerging profession focused on applying data science to prevent, detect, and remediate expanding and evolving cybersecurity threats. CSDS is increasingly formally recognized as a cybersecurity job specialty, for instance in the NIST NICE Cybersecurity Workforce Framework.

A proposed CSDS definition derived from…

I prefer to structure my code the same way as an article, and if have academic background as well, you can relate. Hence, I usually start with preamble, where I put all the packages and toolkits I would like to use. Then, the main part follows and subsequently the rest (for example, where the result of the model should go, all the connections). Especially if you are getting started and learn python, I recommend to structure and comment your code as clear as possible. With Jupiter you have…

Imagine, you are the first data scientist in a company, may be in the industrial company, in one of the old industries, old economy branches. Then, you are a unicorn. Basically, you start data science from the scratch: you must introduce, explain, promote and establish data science. To manage this challenging task, dare to simple!

Three years ago, I was exactly there – the first and for some time the only data scientist in the traditional, old industry company. The challenge was to…

Summary:  AI/ML itself is the next big thing for many fields if you’re on the outside looking in.  But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.

“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most…

There seem to be countless articles projecting the incredible economic and social growth that will be driven by AI.  For example, PwC predicts that AI technologies and applications will increase global GDP by up to 14% between now and 2030 (see Figure 1).

Figure 1:…

Actually the unlocking of hidden benefits and true potential of the data is an essential task for business. Also, customers` satisfaction appears to be a pushing force for evolution of services and products. If you have loads of customer data available for analysis the work on the improvement of the customers` satisfaction…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

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• The true…

Why do we take logs of variable in Regression analysis?

We should remember that a regression equation has two parts

i) The Dependent variable (Predictand)

ii) The Independent variables (Predictors) ; which can be one or more and can be of different types (Categorical or Continuous).

The nature of the regression that we should run depends on the type of Dependent variable that we are dealing with in our model. For example, if the dependent variable is Continuous…