Tag: environment

Feed: Featured Blog Posts - Data Science Central. Author: Henrik Skogström. A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining tasks were laborious and cumbersome, but machine learning has come a long way in a short time. Things have changed with the adoption of more sophisticated MLOps solutions. Now, the common practice of retaining a machine learning model is somewhat reversed. Models are being trained more often and after very short intervals. MLOps solutions have brought about this change with easy access to automation ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. Okay, I'm as mad as hell, and I'm not going to take this anymore! If data scientists are the modern-day alchemist who turn data into gold, then why are so many companies using leeches to monetize their data? When I talk to companies about the concept of a “Chief Data Monetization Officer” role, many of them look at me like I have lobsters crawling out of my ears.  “Sorry, we don’t have that role here.”  Of course you don’t have that role, and that’s why you SUCK at monetizing data.  ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Howard M Wiener. A recent Wall Street Journal article, entitled Coronavirus Pandemic Helps Speed More CIOs Toward Business Operations Accountability, observed: “Large businesses are starting to hold their chief information officers accountable for the results of corporate-wide digital business operations, giving them much wider responsibility within the organization. . . Gartner, which last month released its annual list of top strategic predictions, said that by 2024, a quarter of the CIOs working in large, traditional enterprises will effectively become, as the research and advisory firm calls it, ‘COO by proxy.’” The ... Read More

Feed: R-bloggers. Author: eoda GmbH. As digitalization progresses and data science interfaces continue to grow, new opportunities are constantly emerging to reach the personal analysis goals. Despite the „modernity“ of the industry, there is now a wealth of software for every need: From the design of the analysis infrastructure to the complete, decentralized evaluation through e.g. cloud computing (the outsourced evaluation of analysis scripts). Especially for companies that are just beginning to gain a foothold in the data science and analytics world, it is often difficult to select the appropriate tools and processes for their analysis workflow. But first and ... Read More

Feed: R-bloggers. Author: tomaztsql. [This article was first published on R – TomazTsql, 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. Using multiple languages is a huge advantages when people choose notebooks over standard code files. And with notebooks in Azure Data Studio without switching the kernels, you can stay on one and work your code by using following functions for switching. %%lang_r %%lang_py First, installing the Azure Data Studio . In addition, ... Read More

Feed: R-bloggers. Author: R Bloggers on Francisco Bischoff. In March, 12th, Github has launched the Github Classroom platform. TL; DR, you can continue. For the long story, click here. Classroom For those that want to know more about the capabilities of Github Classroom, I recommend you start here. Using RStudio Why do we need this tutorial? Well, Github Classroom already allows an auto-integration with Microsoft MakeCode and Repl.it, but we, as R developers, like RStudio, right? So how to solve this? The current solution uses mybinder.org as the cloud service that will create our RStudio session. If someone finds out ... Read More

Feed: Recent Announcements. AWS Managed Services (AMS) can now operate AWS workloads hosted on AWS Outposts in your datacenter, co-location space, or on-premises environment. You can accelerate your migration to the cloud with AMS managed IT services for AWS Outposts hosted resources, including incident, problem, patch, and security management. AMS takes responsibility for managing AWS Outposts and resources hosted on AWS Outposts while providing a simple API for provisioning new capacity, requesting changes, and reporting incidents ... Read More

Feed: AWS Big Data Blog. Data is ubiquitous in businesses today, and the volume and speed of incoming data are constantly increasing. To derive insights from data, it’s essential to deliver it to a data lake or a data store and analyze it. Real-time or near-real-time data delivery can be cost prohibitive, therefore an efficient architecture is key for processing, and becomes more essential with growing data volume and velocity. In this post, we show you how to build a scalable producer and consumer application for Amazon Kinesis Data Streams running on AWS Fargate. Kinesis Data Streams is a fully ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Jobin George. By Jobin George, Sr. Partner Solutions Architect at AWSBy Deepak Ram, Director, Strategic Solutions at InformaticaBy Louis-Noël Trapadoux, Principal Product Manager at Informatica Systems are growing more complex, cloud applications are growing in adoption, and cloud data lakes are being increasingly deployed. At the same time, organizations need to implement data cataloging solutions to provide data governance, data analytics, or pure metadata management. These cataloging solutions should be able to quickly start providing insights so they can drive adoption. This adoption would, in turn, provide additional insight into the data assets ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Kirsten Lloyd. There are several narratives that permeate around AI today. It has great promise, but it is not without pitfalls. Many early adopters have invested millions, but remain unimpressed and discouraged by the lack of returns thus far. With that said, and despite the challenges, the community has identified the problematic areas in the process, and a solution is emerging to getting through last mile AI challenges to scale to the enterprise: ModelOps. ModelOps tools manage the last mile delivery challenges associated with deploying, managing, and monitoring AI models into ... Read More