Category: Featured

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. The Digital Shopfloor: Industrial Automation in the Industry 4.0 Era looks like a great free open access book by John Soldatos,  Oscar Lazaro and Franco Antonio Cavadini The book deals with the transformation of the shop floor and the wider supply chain by the deployment of Industrial IoT Some of the themes covered by the book include: Introduction to Industry 4.0 and the Digital Shopfloor Vision Open Automation Framework for Cognitive Manufacturing Reference Architecture for Factory Automation using Edge Computing and Blockchain Technologies Communication and Data Management in Industry ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing. A little reminiscence, or for those of you who are only recently data scientists, a little history lesson.  Our profession of finding the signal in the data, be that supervised or unsupervised got underway in the 90s.  In the last 20+ years we’ve been called by a variety of names.  It’s not at all clear that as those ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. Sustaining industry averages and benchmarks are the antithesis of innovation and a great way to ensure average performance. Doing whatever everyone else is doing is a “paving the cow path” management mentality, lacking aspirational goals which are critical for organizations to fuel innovation and create customer and market differentiation. Which brings me to why I teach. As my students and I work through their “Thinking Like a Data Scientist” exercises together, I always learn something new from them. And not one of these students – tomorrow’s business and society ... 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.   Announcements Data-informed decisions can lead to greater business success. Take the lead in your organization and your career with an online Certificate in Business Analytics from Michigan State University. With two certificate track options, you can pick the path that’s right for you. Start your future today! Would you like to learn the mathematics behind machine learning to ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Stephanie Glen. At the time of writing, I'm a 52 year-old working in the fields of mathematics and data science. In mathematics, that makes me well-seasoned (and probably well-tenured, if I had chosen to continue in academia). In data science, some would consider me a dinosaur. In fact, many older people considering a career in data science might be put off by the thought that data science is tough to break into at a later age. But is that statement true? Should the over 50 crowd put down their textbooks and ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Igor Bobriakov. A successful business requires new approaches to data management in this age. Modern advances in data science area provide an efficient solutions for numerous use cases. Data science embraces a broad spectrum of tasks in the sphere of public administration and brings new opportunities to this field. Let us take into consideration key data science use cases in administration to clear out this term based on practical examples. Considerable attention is paid to fraud detection and prevention in the sphere of public administration. When it comes to the public ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: David Harris. In my prior blog post, I wrote of a clever elf that could predict the outcome of a mathematically fair process roughly ninety percent of the time.  Actually, it is ninety-three percent of the time and why it is ninety-three percent instead of ninety percent is also important. The purpose of the prior blog post was to illustrate the weakness of using the minimum variance unbiased estimator (MVUE) in applied finance.  Nonetheless, that begs a more general question of when and why it should be used, or a Bayesian ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Pablo Gutierrez. When ever we visit a client and present our proposal, we start wondering if it will be accepted or rejected by the customer. Usually, our customer will analyze our proposal, compare it with other competitors’ and make a decision. In order to build our commercial forecast system, we need to assign a probability to every proposal we have presented and assign a numerical value to every one of them.One way of doing this is multiplying the value of the proposal by the probability of wining it. Expected_income=proposal_value* proposal_probability But, ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sameer Nigam. In this article, we will talk about How Spotify is using Artificial Intelligence and Machine Learning to enhance the experience of listeners? How it is helping artists and creators? Which machine learning, loss function, training model technologies Spotify uses in its different applications. What Spotify is planning to do in the upcoming future? Spotify is a music streaming industry started in 2006. It got its first official launch in India in February 2019 and it already had millions of subscribers in its list. Spotify is known for its user ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Lucas Finco. (I will give you a hint. It’s in the name.) Scientists! This post is intended as a response to an interesting discussion on LinkedIn started by analytics manager at Ford, Michael Cavaretta.  https://www.linkedin.com/posts/michael-cavaretta-ph-d-795a965_indus....  He asked what hires make the best data scientists. In my real-world experience in the data science field, I find that physicists make the best data scientists.  Why?  Because physicists work at the intersection of math and reality.  They have been trained to hypothesize ideas about how things work, and then to design experiments to test ... Read More