Feed: Featured Blog Posts - Data Science Central. Author: Kartik Patel. Citizen Data Scientists represent a new breed of business analysts – a group of individuals with diverse business responsibilities and training, who wield sophisticated analytical tools, and employ complex methods of analysis to improve business results – all without the training or assistance of data scientists or IT team members. Citizen Data Scientists are business users who leverage the knowledge and skill they have developed through professional training and business roles to navigate business intelligence and advanced analytical tools to answer business questions, identify trends and patterns and develop new competitive ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Aileen Scott. Diversity and inclusion (D&I) increasingly are becoming a focus area for businesses. And it is not just because it is the right thing to do, but it also makes excellent business sense. According to McKinsey, the top quarter of companies on the diversity list were 33 percent more likely to be among the most profitable in their industries. Also, in the world of startups, diverse founding teams earn 30 percent higher returns for their investors.  Why is D&I important?  This is because it is an essential part of creating ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Andrea Manero-Bastin. This article was written by Matthew Hughes.  CS 106A is Stanford University’s introductory programming course. The module – which is also available to view on YouTube – introduces the fundamentals of coding in an accessible way, and lays the foundations for future growth. Throughout its existence, the course was taught using the Java programing language. Java is popular, certainly, but it’s also extremely clunky and syntactically bloated. But a new version of the course, CS 106J is based on JavaScript. According to the University website, “[CS 106J] covers the same material ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Andrea Manero-Bastin. This article was written by Carlos E. Perez. In this post I will explore further the characteristics of Artificial Intuition with the goal of describing a set of patterns that can aid us in formulating novel architectures for Deep Learning. In a previous post, I introduced the idea that there are two distinct cognitive mechanisms, one based on logical inference and another based on intuition. At least 6 decades have been spent exploring cognitive mechanisms based on logical inference without making much progress towards AGI. Deep Learning, a breakthrough ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Here I share my predictions as well as personal opinion about the pandemic. My thoughts are not derived from running sophisticated models on vast amounts of data. Much of the data available has major issues anyway, something I am also about to discuss. There are some bad news and some good news. This article discusses what I believe are the good news and bad news, as well a some attempt at explaining people behavior and reactions, and resulting consequences. My opinion is very different from what you have read ... Read More

Feed: SAS Blogs. Author: Matthew Stainer. "We could have a session, on a new 'cool' machine learning technique". A while ago, when discussing sentiment analysis and how individuals phrase things differently, a colleague of mine dryly noted: "for Jason everything is cool, the day Matthew describes something as cool, then I'll take notice". In my defence, I think 'cool' is a subjective thing. I think that Sebastião Salgado's photography is cool, as is Cognitive psychology, 1990's Trip Hop music and a 'cool' day for me, can be one spent pottering in my garden. But I'll admit it's not a word I use ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Logan berger. The pandemic has shown how vulnerable our supply chains are. A small interruption can bring a supply chain to a halt, which in today’s fast-paced world, is simply not acceptable. Customers are always expecting their product to arrive on time when ordered, and any delay in the supply chain can have significant consequences for organisations. What today’s supply chains require is speed, agility and flexibility to respond quickly to changes in demand. The pandemic has shown us that demand and requirements can change rapidly, and those organisations that were ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Kurt Cagle. Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were designed to generate various types of printed output. Over the years, the library has been adapted for different platforms and roles, and today is still one of the most widely used network graph visualization tools around. One of the most common libraries associated with graphviz is the DOT ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Robert R. Tucci. Recently, someone (not me) suggested in a tweet to Judea Pearl, let's have a Kaggle** competition on the topic of Causal AI. I love the idea, so I am trying to promote it with this blog post. Big Pharma could fund such a competition for much less than what they pay for a TV commercial, and the technical insights they might gain from this exercise might prove to be invaluable to the pharmaceutical industry. (Plus it would be good publicity for them, much better than a lame TV ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Robert R. Tucci. Daphne Koller is the leader of a mega-startup (Insitro) that uses Machine Learning (do they use Causal Bayesian Networks???) to do drug research. She also co-founded Coursera with Andrew Ng, and she co-wrote with  Nir Friedman a 1200 page book about Probabilistic Graphical Models (e.g., Bayesian Networks) Judea Pearl won a Turing award (commonly referred to as the Nobel prize of computer science) for his work on Bayesian Networks and Causal AI. Recently, I posted a Tweet about Daphne Koller to which Judea Pearl responded with a question ... Read More