Author: Data Science Central

Feed: Featured Blog Posts - Data Science Central. Author: Frank Raulf. The importance of completeness in linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent. Assuming a linear complete model of the form: z = a + bx + cy + ε. Where z is supposed to be dependent, x and y are independent and ε is the error term. Now we drop y to check which terms are affected. By reducing one dimension we transform a linear hyperplane to a linear line. In the initial R3 this two-dimensional line (incomplete model) is located ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Igor Bobriakov. Programming languages are a tool for the realization of many powerful data science applications. But, there are so many of them and it has become confusing to choose the optimal one for your specific project. In this article, we are going to talk about popular languages for Data Science and briefly describe each of them. Python Python is a modern, general-purpose, high-level, dynamic programming language. It can be used for integrating with web apps or incorporate statistics code into a production database. There are a lot of libraries, which can ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Shady Johnson. The Internet of Things (IoT) has revolutionized the world we live in. Every global industry has the impact of IoT on it that only aims to increase the efficiency of business operations and provide better user experience ultimately. Apart from automated cars and retail stores interconnected over a global network, IoT has the potential of affecting the global supply chain and the management in a way that only causes an increase in the efficiency and delivers better results. Supply Chain Management With IoT According to Gartner, by 2021, one ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Roman Chuprina. Artificial Intelligence and Machine Learning solutions offer large possibilities to optimize and automate processes, save costs and make less human error possible for many industries. Food and Beverage is not an exception, where it can be beneficially applied in restaurants, bar and cafe businesses as well as in food manufacturing. These two segments have common use cases where AI in the food industry can be applied, as well as different ones, which is linked to different problems that must be solved. Contents of this article 1 Start from food market ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. One of the biggest threats to our world economy (outside of climate change, social inequality, unregulated proliferation of weapons and the rise of Terminators), is the retirement of the technician and engineering expertise that is necessary to keep our factories, hospitals, cities, trains, airports and other operational entities running effectively.  Deloitte’s 2018 skills gap in manufacturing study found that the skills gap may leave an estimated 2.4 million positions unfilled between 2018 and 2028, with a potential economic impact of $2.5 trillion worldwide (see Figure 1). Figure 1:  Deloitte’s  ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Lewis Wynne-Jones. A few years ago I took a call from an analyst at a hedge fund who was looking for external data that would, in his words, provide “alpha.” I explained that our company was connected to thousands of data sources and hundreds of thousands of public datasets; I told him that we were continuously pulling in open data from 70 countries, standardizing it through an ingestion pipeline trained against the largest catalogue of public data in the world, and serving it up via a suite of APIs that plug ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Igor Bobriakov. In the times when data is of extreme value, industries cannot afford to ignore it. The only right choice for them is to find new ways to use data for their benefit. These words have become a motto for the sales industry along with the others. As far as the feature of the repetitiveness may characterize sales industry, there are numerous dimensions where data science may be applied. All in all, data science brings growth, improvements, efficiency, and effectiveness in sales. Thus, the collective dream of all those dealing ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Capri Granville. Gradient Descent has a problem of getting stuck in Local Minima. The following alternatives are available. The following is a summary of answers suggested on CrossValided, originally posted here.  Source for picture: here First answer There are many optimization algorithms that operate on a fixed number of real values that are correlated (non-separable). We can divide them roughly in 2 categories: gradient-based optimizers and derivative-free optimizers. Usually you want to use the gradient to optimize neural networks in a supervised setting because that is significantly faster than derivative-free optimization. There are numerous gradient-based ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Booze Allen just launched a one-stop shop for all manner of pretested DNN models.  They’re even guaranteeing price.  This makes buying just like picking accounting, CRM, or HRIS software.  Equally as important, it’s a genius example of platform strategy to lock in customers and lock out competitors. The common vision of developing and deploying a deep learning model is half-a-dozen (at least) data scientists and engineers slogging away over maybe three to six months before having that MVP to first test in production. Not anymore.  Go down to ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. Artificial Intelligence – Cloud and Edge implementations takes an engineering-led approach for the deployment of AI to Edge devices within the framework of the cloud. We often use the word ‘engineering’ in casual conversation. However, in this context, we attach a specific meaning to Engineering. Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and buildings. The American Engineers' Council for Professional Development defines engineering as: (specific emphasis of interest highlighted) The creative application of scientific principles to design or develop structures, ... Read More