Predictive analytics is a wide field of techniques that share a common goal of predicting future behavior. Choosing the right prediction modeling method is perhaps the most important step in the process, because predictive models are the driving force behind predictive analytics. This picture summarizes six of the most popular methods:…

Today, one of the most popular tasks in Data Science is processing information presented in the text form. Exactly this is text representation in the form of mathematical equations, formulas, paradigms, patterns in order to understand the text semantics (content) for its further…

Thomas Edison famously said that success is 90% perspiration and 10% inspiration. That’s nowhere truer than in machine learning. Even though the hype around artificial intelligence has never been higher, the reality of what it takes to actually work in the field - and what it takes to use it successfully - is mired in confusion.

Indeed, hype makes it look like 100% inspiration; it hides the work involved in building knowledge and learning skills.

So, to help tackle that, here…

This post is the third one of a series regarding loops in R an Python.

The first one was Different kinds of loops in R. The recommendation…

Ah, it’s that time of year when everyone is making predictions about next year and extrapolating from the previous year’s trends to create logical, pragmatic predictions. I’ve already made my own predictions for 2020 in the article, “AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020,”where I predicted the following

Main 2019 Developments:

• Growing "consumer proof points" with respect to AI…

Thinking of data science as merely a technical profession, like programming, may take you away from your goals. Focusing on the usability of mathematics for data science before jumping into full-fledged math courses will save you a lot of time.

I wrote this blog post because I made a few mistakes while starting…

Academia and industry take different approaches to building machine learning and deep learning models

Here are seven differences

1) Approach to accuracy:…

Production sphere embraces a wide range of processes related to all branches and stages of creating material goods. In addition, these material goods may be of different values and even have rather contrasting goals. 

Under conditions…

Data science and analytics are growing in their popularity and range of applications in the modern world. Data science deals with answering questions and uncovering hidden insights, while analytics is rather concentrated on the processing itself and conducting of statistical…

If you ask the question "What's the best degree for Data Science?" you'll get dozens of different answers. The sheer amount of different opinions might leave you wondering which degree is the "best", and there isn't a simple answer.  One person's "best" degree is another person's "worst."

Trying to make sense of all those differing opinions? I've done the hard work for you. This is where statistics is actually very useful (and it's one of the popular choices for…

For years we have seen artificial intelligence appear in many films and television series, but in recent years is seen in a more remarked, even going further, we talk about Algorithms. Such is the case, that in the last Disney film of the Rompe Ralph series, the character of Yesss appears, representing an Algorithm as we understand it nowadays.

Next, I'll tell you about the films I've seen and there are specific mentions of our world:…

I share a list of recommended free books for Data Science & AI from introductory level to advanced techniques:

• The LION Way: Machine Learning plus Intelligent Optimization
• Computer Vision…

With the start of the Liga Santander in Spain, I share a very interesting R library that I share with the community in social networks  @Vdot_Spain for all the analysts and data scientist of the football world.

According to @Vdot_Spain: "soccergraphR v0.1 MVP is the first step in helping analysts, journalists, and clubs understand and manage @OptaJose information with #Rstats. You can install it from…

Summary:  There have been several stories over the last several months around the theme that AI is about to hit a wall.  That the rapid improvements we’ve experienced and the benefits we’ve accrued can’t continue at the current pace.  It’s worth taking a look at these arguments to see if we should be adjusting our plans and expectations.

 …

H2O is a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks. The dataset we are using is the Bank Marketing Dataset. Here we need to train a model which will be able to predict if the client of the bank opens…

The ability of companies to provide great healthcare has always been reliant upon data. Before the widespread adoption of technology, important information came from medical exams, checkups, and direct communication between physicians. …

By Faruqui Ismail and Nooka Raju Garimella

Reporters with various forms of "fake news" from an 1894 illustration by Frederick Burr Opper

We’ve always pictured the rise of artificial…

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.  …

AI is a game changer. Period. And being a data and analytics guy, I could not be more excited about it.

The McKinsey research study “Notes from the AI frontier: Applications and value of deep learning” provided some valuable insights into where and how Artificial Intelligence (i.e., Deep Learning / Neural Networks (CNNs, RNNs, GANs), Reinforcement Learning and Deep Reinforcement Learning) will derive and drive new sources of customer, product and…