Tag: distribution

Feed: Journey to AI Blog; Author: Carmen-Gabriela Stefanita; The Distribution Sector faces inherent challenges around delivering timely value, asset management, supply chain operations, customer segmentation and how to make use of the immense amounts of data interwoven throughout.   The economic environment experienced in 2020 magnified these challenges and introduced new customer experience demands that can only be met through hyper-personalization. Companies continually look to optimize operations while also focusing on the needs of each customer. The future of distribution requires overcoming complexity in your business, including: Overwhelming data. Large sets of data are coming in at an unprecedented rate and ... Read More

Feed: AWS Compute Blog. Author: James Beswick. In the Operating Lambda series, I cover important topics for developers, architects, and systems administrators who are managing AWS Lambda-based applications. This two-part series discusses core security concepts for Lambda-based applications. Part 1 explains the Lambda execution environment and how to apply the principles of least privilege to your workload. This post covers securing workloads with public endpoints, encrypting data, and using AWS CloudTrail for governance, compliance, and operational auditing. Securing workloads with public endpoints For workloads that are accessible publicly, AWS provides a number of features and services that can help mitigate ... Read More

Feed: Planet MySQL; Author: Saroj Tripathy; This blog is about table partitioning in NDB Cluster. We will see how this feature has been enhanced from version to version. Also we will see which partitioning user should use under which scenario. Here I will assume that the user has some knowledge on NDB cluster.Data distribution and table partitioning are usually coupled together. In NDB, when we talk about table partitioning, we mean ‘data distribution’ mainly as NDB doesn’t fully support RANGE, HASH or LIST partitioning. Most of the enhancements made to partitioning over the years are about ‘data distribution’ rather than ... Read More

Feed: CIO. Author: . COVID-19 struck IT like a tsunami in early 2020, sweeping away long-established operations and processes, forcing CIOs to quickly identify and deploy acceptable alternatives. Now, as the virus threat appears to be gradually receding, IT leaders are viewing a radically transformed landscape, wondering how essential operations and practices will fit into a “new normal” business world.The pandemic reshaped enterprises in an almost endless number of ways. IT, too, has felt the impact, leaving CIOs to wonder how their departments will cope with and function in a post-virus world. With basic changes already appearing, here’s a look ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. This blog is the second part in a series. The first part is The Bayesian vs frequentist approaches: implications for machine le... In part one, we summarized that: There are three key points to remember when discussing the frequentist v.s. the Bayesian philosophies. The first, which we already mentioned, Bayesians assign probability to a specific outcome. Secondly, Bayesian inference yields probability distributions while frequentist inference focusses on point estimates. Finally, in Bayesian statistics, parameters are assigned a probability whereas in the frequentist approach, the parameters are fixed. Thus, in ... Read More

Feed: R-bloggers. Author: Ivan Svetunkov. [This article was first published on R – Open Forecasting, 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. Since the previous post on “The Creation of ADAM“, I had difficulties finding time to code anything, but I still managed to fix some bugs, implement a couple of features and make changes, important enough to call the next version of package smooth “3.1.0”. Here is what’s new: A new ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Alaa Mahjoub. In many cases, for an enterprise to build its digital business technology platform, it must modernize its traditional data and analytics architecture. A modern data and analytics platform should be built on a services-based principles and architecture. Introduction part 1, provided a conceptual-level reference architecture of a traditional Data and Analytics (D&A) platform. This part, provide a conceptual-level reference architecture of a modern D&A platform. Parts 3 and 4, will explain how these two reference architectures can be used to modernize an existing traditional D&A platform. This will be ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: akash. Increased consumption of data, more powerful computing, and the strong inclination towards data-driven decisions in business have made data science a crucial part of today's business environment. According to IBM, there is a huge demand for data scientists and data analysts in the present time. Python and R are the two most popular tools for programming for data science. Python and R both are open-source and free and were developed back in the early 1990s. For practitioners of machine learning and data science, these two tools are absolutely essential. While ... Read More

Feed: R-bloggers. Author: R on OSM. [This article was first published on R on OSM, 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. We start a new series on neural networks and deep learning. Neural networks and their use in finance are not new. But are still only a fraction of the research output. A recent Google scholar search found only 6% of the articles on stock price price forecasting discussed neural networks ... Read More

Feed: R-bloggers. Author: Higher Order Functions. [This article was first published on Higher Order Functions, 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. For a long time, I’ve been curious about something. It is a truth I’ve seen casually dropped in textbooks, package documentation, and tweets: random effects and penalized smoothing splines are the same thing. It sounds so profound and enlightened. What does it mean? How are they the same? What deep ... Read More