Category: Featured

Feed: Featured Blog Posts - Data Science Central. Author: Ronald van Loon. As a long-time part of this industry, I have spent a good part of the last decade talking about the digital transformation. Call it the digital transformation or the data-led transformation, but this transformation has been the talk of the town for a long time now.  Not only are organizations geared toward achieving a better analytics setup, but they are also on the lookout for a more efficient data policy in the process. With many cloud service providers around us offering AI as a service, companies can tap ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Adetayo Kolade. Power BI provides slicers for a single column, but there are scenarios where it could be useful to consolidate alternative filters for multiple columns in a single slicer. Technically, this is not possible in Power BI through the standard visualizations, but you can use a particular data modeling technique to obtain the desired result.Consider the case of a Customer table with a geographical hierarchy with Continent, Country, and State. The requirement is to enable a filter over California (State), France (Country), or Asia (Continent) using a single slicer, as shown in the ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Olha Zhydik. One of the things that excite the most about the predictive analytics of today is how quickly and bluntly it surpasses the existing benchmarks. Moreover, it penetrates the industries and activities where human creativity has traditionally dominated, adding a futuristic touch to the music, fine arts, fashion or architecture. Following the popular trend, we decided to explore the current capabilities of neural networks and find out if they can be of some real value for the fashion industry. Short time, big results In 2015, Google’s research team developed the DeepDream ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.   Featured Resources and Technical Contributions  40+ Modern Tutorials Covering All Aspects of Machine Learning New Notebook: Deep Learning and Computer Vision with CNNs (Convolutional Neural Networks) Bayesian Machine Learning - Part 7 New Notebook: Getting Started with TensorFlow 2.0 Difference Between Correlation and Regression in One Picture Implementing Linear Regression with Golang Understanding Dataflow graphs in TensorFlow Creating a ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Aaron Burciaga. We live in a world driven by insights and decision making fueled by data and analytics. Information and technologies are so ubiquitous that no organization needs to be a digital titan (such as Amazon or Google) to compete in today’s world of business. Companies, large and small, are recognizing the need to utilize the full value of their enterprise data to obtain an essential competitive edge. Since business competition can be fierce, it is now, more than ever, necessary for a company to be able to adeptly appropriate data assets ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sandy Bridgwater. Because of the advancements in machine-learning based image recognition and AI-driven optimization, the influence of big data in the context of computer science is given a lot of attention. But today, we will explore the effect of big data on one of the most exciting fields of science. Astroparticle physics has been the arena for 5 Nobel Prize winners in the last 20 years, due in no small part, according to Dr.Bradley Kavanagh, to developments in big data. Bradley Kavanagh is an astroparticle physicist working at the University of ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Packt Publishing. In order to be a highly efficient, flexible, and production-ready library, TensorFlow uses dataflow graphs to represent computation in terms of the relationships between individual operations. Dataflow is a programming model widely used in parallel computing and, in a dataflow graph, the nodes represent units of computation while the edges represent the data consumed or produced by a computation unit. This post is taken from the book Hands-On Neural Networks with TensorFlow 2.0 by Ekta Saraogi and Akshat Gupta. This book by Packt Publishing explains how TensorFlow works, from basics ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. Leverage AI to Create Autonomous Policies that Adapts without Human Intervention Policies are the foundation for any successful organization.  Policies are the rules, or laws, of an organization.  Policies document the principles, best practices and compliance guidelines that aid decision-making in supporting the consistent and repeatable operations of the business. Heck, one could argue that an organization’s culture is better defined by its policies than it is by the character of its leadership team. Unfortunately, the management, creation and execution of policies haven’t changed much since the days of ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Ronald van Loon. Organizations across the globe are buzzing about the cloud as the savior of their data management needs that provides them with the assistance they require for their business solutions. In this digital era of insights and analytics, the cloud has emerged as the best possible source for data management.  However, the suitability of the cloud for data management does not mean that you should jump toward it without doing some of your own homework. Organizations should know what they are stepping into, and all the options they have ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Packt Publishing. Did you ever wonder why linear regression plays an important role in statistics and machine learning? It is witnessed that linear regression is one of the most commonly and well-understood algorithms.  Regression is a statistical method for calculating relationships among variables. It is one of the most popular and simplest regression techniques and is a very good way to understand your data. Note that regression techniques are not 100% accurate even if you use higher-order (nonlinear) polynomials. The key with regression, as with most machine learning techniques, is to find a good-enough ... Read More