data science


How Data Science Drives Growth and Improves Customer Experiences in FinServ and Retail

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They use it along with analytics to understand customer behavior and aid real-time decision-making. This achieves better, more goal-oriented results. Businesses may also use data science to reverse negative trends. For example, retailers and financial-services companies can use data science when dealing with bankruptcy, layoffs, or imminent closures. The data may suggest the best courses of action.


Diffusion Map for Manifold Learning, Theory and Implementation - KDnuggets

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'Curse of dimensionality' is a well-known problem in Data Science, which often causes poor performance, inaccurate results, and, most importantly, a similarity measure break-down. The primary cause of this is because high dimensional datasets are typically sparse, and often a lower-dimensional structure or'Manifold' would embed this data. So there is a non-linear relationship among the variables (or features or dimensions), which we need to learn to compute better similarity. Manifold learning is an approach to non-linear dimensionality reduction. The basis for algorithms in manifold learning is that the dimensionality of many data sets is only artificially high 1.


Fighting the Covid-19: All the datasets and data efforts in one place

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Since the corona erupted into our world, research institutes and governments have released many databases publicly to allow research groups (and independent individuals) to analyze the data around the corona's spread. These databases are scattered under numerous initiatives and sources. The purpose of this blog is to organize all the major open databases and data initiatives around the world. Feel free to add it in the comments or through this form. In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19).


How Data Science is Driving Digital Transformation Now - Saturn Cloud

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In an increasingly competitive world, we should have a deep understanding of the business in which we operate, how it is evolving, and the new innovations that we could embrace or build to remain competitive and conquer new market segments. To do this, we must be able to develop a clear vision of transformation that takes us to another level of performance. By embracing Digital Transformation, we will deal with artificial intelligence, machine and deep learning, virtual reality, and a lot of other innovative technologies. At first sight, it might even sound fearful to lead the business in such a complex and intricate direction. With this in mind, we will consider some strategies to better understand and take competitive advantage of the huge streaming of data in the current era of the digital revolution.


Junior Joy He merges data science and mental health

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As an undergraduate research leader, He's mission is to "use Artificial Intelligence to further democratize healthcare and education."


Animated Plots using ggplot and gganimate

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Did you know, that you can transform plain old static ggplot graphs to animated ones? Well you can with the help of the package gganimate by RStudio's Thomas Lin Pedersen and David Robinson and the results are amazing! My STATWORX colleagues and I are very impressed how effortless all kind of geoms are transformed to suuuper smooth animations. That's why in this post I will provide a short overview over some of the wonderful functionalities of gganimate, I hope you'll enjoy them as much as we do! Since Valentine's Day is just around the corner, we're going to explore the Speed Dating Experiment dataset compiled by Columbia Business School professors Ray Fisman and Sheena Iyengar.


The Data Science Venn Diagram -- Drew Conway

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On Monday we spent a lot of time talking about "where" a course on data science might exist at a university. The conversation was largely rhetorical, as everyone was well aware of the inherent interdisciplinary nature of the these skills; but then, why have I highlighted these three? First, none is discipline specific, but more importantly, each of these skills are on their own very valuable, but when combined with only one other are at best simply not data science, or at worst downright dangerous. For better or worse, data is a commodity traded electronically; therefore, in order to be in this market you need to speak hacker. This, however, does not require a background in computer science--in fact--many of the most impressive hackers I have met never took a single CS course.


Statistics for Data Science and Business Analysis

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Statistics for Data Science and Business Analysis, Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis Created by 365 Careers, 365 Careers Team English [Auto-generated], French [Auto-generated], 7 more PREVIEW THIS COURSE GET COUPON CODE 100% Off Udemy Coupon .



Frontier Development Lab Is Going Virtual: Now Accepting Applications For Paid Research Opportunities - SpaceWatch.Global

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The Frontier Development Lab (FDL) Europe applies AI technologies to science to push the frontiers of research and develop new tools to help solve some of the biggest challenges that humanity faces. These range from the effects of climate change to predicting space weather, from improving disaster response, to identifying meteorites that could hold the key to the history of our universe. FDL brings researchers from the cutting-edge of AI and data science, and teams them up with their counterparts from the space sector for an intensive eight-week research sprint, based on a range of challenge areas. The results far exceed what any individual could develop in the same time period, or even in years of individual research. A key aspect of our success is the careful formation of small interdisciplinary teams focused on tackling specific challenges.