methods

The Netherlands' antitrust watchdog on Saturday said Apple Inc will allow different payment methods in Dutch dating applications, ending a dispute that resulted in the company being fined 50 million euros ($52.58 million). The Authority for Consumers and Markets (AMC) said in a statement that with this concession, Apple will meet the requirement that the regulator had set under the European Union and Dutch competition rules. The iPhone maker has long mandated use of its in-app payment system, which charges commissions of…

In what could mark a major step toward solving the problem of freshwater scarcity, scientists have developed a device that filters saltwater a thousand times faster than conventionally used devices. On the industrial scale, seawater is made fit for drinking through the desalination process. It includes removing salt to produce fresh water that is further processed in plants and used for drinking or irrigation. In a recent study, Scientists devised a new method to purify saline water in a faster and more effective…

As machine learning seizes yet another opportunity to beat out human capabilities, Google Ads is officially retiring Expanded Text Ads (ETAs) on June 30. The simple days of three headlines and two descriptions will be replaced by mix-and-match opportunities of up to 15 headlines and four descriptions.  Advantages to running Responsive Search Ads (RSAs) include: The ability to test multiple ad copies at once without the manual labor of setting up different ads.Endless ad…

Let's explore some methods to adapt your parameters over time.Photo by Ross Findon on UnsplashIn this post, I will discuss the ideas behind adaptive parameters methods for machine learning and why and when to implement them as some practical examples using python.Adaptive methods (also known as parameter scheduling) refer to strategies to update some model parameters at training time using a schedule.This change will depend on the model's state at time t; for example, you can set update them depending on the loss value,…

A comprehensive tutorial for learning to leverage powerful model-based imputation techniques.Photo by Anni RoenkaeIntroductionDespite the massive number of MOOCs and other online resources, there are still skill gaps in dealing with certain data problems. One example is properly dealing with missing data in real-world datasets. Beginners often take this problem lightly, and they are not to blame. Even though it is such a pressing issue, the complexity of missing-data problems has significantly been underestimated because…

A couple of techniques to guess if you can use or not a linear model in your ML problemPhoto by Isaac Smith on UnsplashAn essential part of a regression analysis is to understand if we can use a linear model or not for solving our ML problem. There are many ways to do this, and, generally, we have to use multiple ways to understand if our data are really linear distributed.In this article, we will see two different graphical methods for analyzing the residuals in a regression problem: but those are just two methods useful…

In our 2022 research about sentiment analysis, we explained how businesses increasingly invest in sentiment analysis and how it works. One of the challenges of sentiment analysis is multiple languages. As seen in Figure1, majority of the web data is in languages different from English. When it comes to applying sentiment analysis, despite more sources becoming available over time, majority of the sources are primarily available for English and it is challenging to apply sentiment analysis in different languages. In this…

Graphical abstract. Credit: Science of The Total Environment (2022). DOI: 10.1016/j.scitotenv.2022.155694 Previous studies have indicated that soil heavy metals (HMs) contaminating the surrounding of mining areas mainly emanates from industrial emissions. However, research on the quantification of specific risks from various sources is still lacking.…