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Since the dawn of the digital age, the amount of data stored on servers has risen dramatically. More and more firms are looking for talent that can handle their datasets and generate insights for business decisions. Data scientists are among the most popular for this task. Google Trends shows that the global volume of the search term “Data Scientist” has tripled over the last 5 years - but how does the increasing demand translate...
Companies use machine learning to improve their business decisions. Algorithms select ads, predict consumers’ interest or optimize the use of storage. However, few stories of machine learning applications for public policy are out there, even though public employees often make comparable decisions. Similar to the business examples, decisions by public employees often try to optimize the use of limited resources. Algorithms may assist...
Are you looking for real world data science problems to sharpen your skills? In this post, we introduce you to four platforms hosting data science competitions. Data science competitions can be a great way for gaining practical experience with real world data, and for boosting your motivation through the competitive environment they provide. Check them out, competitions are a lot of fun! Kaggle Kaggle is the best known platform...
Curious about neural networks and deep learning? This post will inspire you to get started in deep learning. Why are we witnessing this kind of build up for neural networks? It is because of their amazing applications. Some of their applications include image classification, face recognition, pattern recognition, automatic machine translation, and so on. So, let’s get started now. Machine Learning is a field of computer science that...
The open-source project R is among the leading tools for data science and machine learning tasks. Given its open-source framework, there are continuous contributions, and package libraries with new features pop up frequently. Currently, the CRAN package repository features 12,525 available packages. This post takes a look at the most popular and useful packages that have set the standards for solving data manipulation, visualization, and...
  Currently, Python and R are the dominating data science tools and Python will probably even be taking the lead (at least based on the latest KDNuggets survey ). When did the two open source players manage to become the leading platforms for analytics, data science, and machine learning, leaving behind established players such as Matlab or SAS? Here are some insights from Google Trends. Looking at the years 2009 - 2013 in the...
Big Data, AI and Machine Learning are today's buzzwords. Data nerds, business executives and politicians alike are talking about data-related opportunities and potential risks. But since when has this been the case and how have data-related interests developed over time? We've looked into this question using Google Trends data.  Google searches reveal people's interests Google search queries have become a powerful tool to...
For individuals, businesses and research institutes working with emerging technologies, it is important to follow and shape societal debates revolving around their field. Sooner or later, societal debates are likely to translate into political action, which may greatly impact work on emerging technologies – for better or worse. Also, if research institutes and businesses aim for more than research results and profit, they’re...
Much has been written on the most popular software and programming languages for Data Science (recall, for instance, the infamous “Python vs R battle”). We approached this question by scraping job ads from Indeed and counting the frequency at which each software is mentioned as a measure of current employer demand. In a recent blog post , we analyzed the Data Science software German employers want job applicants to know...
Data science is flourishing in Germany and the demand for data specialists is high and rising. But do regional differences exists and can we identify certain clusters or hotspots? Current job openings may indicate the growth in data science jobs in each region. We downloaded all openings on Indeed to obtain a rough idea of where in the country data science is booming.   // Berlin and Munich are...
One approach to estimate and track employer demand of data science software is to analyze which skills are asked for in job ads. We did this using job ads on Indeed and showed which data science software skills are most in-demand in Germany and worldwide .  In this post, we describe the methods these analyses are based on. We worked with R, as it offers convenient packages facilitating the task.    Searching for...