Blockchain: the single most confusing term since Bitcoin. Everyone has a vague idea of what it does. It’s either the ultimate evolution of financial technologies, or a silly fad that can be summed up in the disconcerting phrase: “dogechain.” In reality, major companies around the world have already shown favor

Narrative Science has been a regular feature on Dataconomy over the past year, from Chief Scientist Kris Hammond’s post about the impact of artificial intelligence on banking, to the launch of their Quill Connect application for processing unstructured text data from social media. I think for AI in general, the goal is not to

Nothing is better than seeing a lowly start­up succeed. They push the envelop, think outside of the box, and inspire. The game, however, can be tough to play. For innovators and techies who don’t necessarily have experience or funding, breaking through can seem impossible. This is why accelerators and incubators

Whether you’re entirely new to the field of big data, or looking to expand your machine learning knowledge; whether you have 3 hours or 3 minutes; whether you want you want to know more about the technology, or the high-level applications- this list is a sample of the best Youtube

What does it take to get into tech’s hottest career path? Over the past year we’ve posted many articles related to getting into Data Science and the related fields. Experts from across the industry have talked about the core technical skills and where they can be acquired. Celebrating the launch

Choosing the right language for data analysis can be almost as complicated as actually learning the language. For many reasons, R and Python are two of the most popular: R is often praised for its great features for data visualization, as it was developed with statisticians in mind; plenty of programmers love multi-purpose Python for its so-simple-a-child-could-do-it syntax. Why

Pandas is the most widely used tool for data munging. It contains high-level data structures and manipulation tools designed to make data analysis fast and easy. In this post, I am going to discuss the most frequently used pandas features. I will be using olive oil data set for this

I’ve previously written a lot on data mining in the abstract; now, I want to start taking you through some practical applications. Welcome to the fascinating world of the recommendation engine- this post will walk through the concepts, and later posts will teach you how to implement your own. What

About Tyler Folkman: I am currently pursuing my masters in computer science at UT Austin with a focus on machine learning and data mining. I am doing research at the intersection of healthcare and data mining as a member of the IDEAL lab and work part-time at Cognitive Scale. This tutorial

This article originally appeared at Sharp Sight Labs. Follow Joshua Ebner, the founder of Sharp Sight Labs, on Twitter. Read more here. Over and over, when talking with people who are starting to learn data science, there’s a frustration that comes up: “I don’t know which programming language to start