Tag: data science

Feed: R-bloggers. Author: Lou Bajuk. [This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Photo by Stillness InMotion on Unsplash In previous posts, we’ve talked about the critical importance of interoperability, and how it helps organizations and data science teams get the most out of their analytic investments. We’ve focused recently on the ways that R and Python can be used together, and how RStudio’s products ... Read More

Feed: Journey to AI Blog; Author: Jennifer Clemente; IBM has been named a Leader in the Gartner February 2021 Magic Quadrant for Cloud AI developer services. Recently, IBM is also recognized as a Leader in two other recently published Gartner Magic Quadrant reports : August 2020 Magic Quadrant for Data Integration Tools and March 2021 Magic Quadrant for Data Science and Machine Learning Platforms. In its latest Magic Quadrant, Gartner defines ‘cloud AI developer services’ as “cloud-hosted or containerized services/models that allow development teams and business users to leverage artificial intelligence (AI) models via APIs, software development kits (SDKs), or ... Read More

Feed: Neo4j Graph Database Platform. Author: Enzo. We have added a new certification exam for Neo4j Graph Data Science on Neo4j GraphAcademy.There is a growing community of developers and data scientists who are using the Neo4j Graph Data Science Library to perform analysis of their graph data. The Neo4j Graph Data Science Library contains many graph algorithms that Neo4j provides full support for, as well as algorithms that are implemented, but not fully-supported (alpha/beta).You can become certified in Neo4j Graph Data Science to demonstrate to your colleagues you have this high-in-demand skill.About the ExamThe Neo4j Graph Data Science Certification exam ... Read More

Feed: Journey to AI Blog; Author: Rathnakumar Udayakumar; The latest Gartner Magic Quadrant for Data Science and Machine Learning Platforms has just been released, and IBM is delighted to be recognized as a Leader in the space. Watson Studio on IBM Cloud Pak for Data, a modular, open and extensible platform for data and AI that combines a broad set of descriptive, diagnostic, predictive and prescriptive capabilities. Organizations seeking to more efficiently run and manage AI models, simplify their AI lifecycle management, and empower their data scientists with technology that can help optimize their data-driven decision-making can turn to IBM ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. It is not yet clear what lasting impact the Covid-19 pandemic will ultimately have on R conferences. We are still adapting to our inability to attend large events, and trying to make the best of the “silver lining” of virtual events which permit worldwide participation. The following is an attempt to list ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Source: see here Part 1 of this short series focused on the business analytics / BI / operational research aspects, see here. In this Part 2, you will find the most interesting machine learning and statistics articles that I wrote in the last few years, focusing on core technical aspects. The whole series will feature articles related to the following aspects of machine learning: Mathematics, simulations, benchmarking algorithms based on synthetic data (in short, experimental data science) Opinions, for instance about the value of a PhD in our field, or ... Read More

Feed: R-bloggers. Author: R Consortium. [This article was first published on R Consortium, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Join us March 18, 9:00 a.m. – 10:30 a.m. PDT. More information! The role of data journalists in the scientific process has traditionally been overlooked. However, the most recent pandemic showed how journalism shapes scientific responses and public policy. Thousands of journalists rose to the challenge when the public needed information in ... Read More

Feed: Journey to AI Blog; Author: Cristina McComic; AI adoption is critical for business success in the changing, competitive market. A HIMMS and IBM study found that 64% of respondents said their organizations placed a “critical” or “high” strategic priority on AI. However, many organizations are still reluctant to fully adopt AI into their processes and decision-making for fear of the unknown. “To many who aren’t data scientists, AI is still a black box and that scares us,” says Kelly Combs, Director of Emerging Technologies Risk Services at KPMG. So how do organizations go about establishing trust in their AI? The ... Read More

Feed: R-bloggers. Author: Akosua Boateng. [This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Photo by JD Long We are excited to announce the fourth formal summer internship program at RStudio. The goal of our internship program is to enable RStudio employees to collaborate with current students to do impactful work that not only helps both RStudio users and the broader community, but ensures that the ... Read More

Feed: SAS Blogs. Author: Josefin Rosén. Artificial intelligence is a powerful force for good and an extraordinary competitive advantage. But, as Peter Parker’s uncle Ben nicely put it, "With great power comes great responsibility.” Or as my friend the Swedish character Pippi Longstocking says, “If you are very strong you must also be very kind!” They are both onto something important: It is important to use powerful techniques responsibly. Bias in data leads to bias in output All humans are biased by nature. By bias, I simply mean our prejudices and preconceived opinions that we use, for instance, when we ... Read More