Tag: Deep Learning

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. It is sometimes said that you don't need to know math to be a data scientist. Sometimes the opposite is said, after all, data science is supposed to be a science! Regardless, below are a few of my articles featuring how data science and math can benefit from each other - not just math to solve data science problems, but also data science to solve math problems. Articles Variance, Attractors and Behavior of Chaotic Statistical Systems New Family of Generalized Gaussian Distributions Gentle Approach to Linear Algebra, with Machine ... Read More

Feed: R-bloggers. Author: Super User. Last week, we updated package ruimtehol on CRAN. The package provides an easy interface for R users to Starspace which is a general purpose neural embedding model for text data. Notable changes are that the package now also builds fine on Mac OS and runs fine on all CRAN platforms. If you are interested to see what the package can do, have a look at the presentation below or visit the package vignette at https://cran.r-project.org/web/packages/ruimtehol/vignettes/ground-control-to-ruimtehol.pdf   If you like it, give it a star at https://github.com/bnosac/ruimtehol and if you need commercial support on text mining, get in touch. Upcoming training ... Read More

Feed: R-bloggers. Author: Douglas Pestana - @DougVegas. Data Scientists and Analysts are starting to overflow their cups with mostly non-value added work at the request of stakeholders. And many don’t have the courage or confidence to say “No” to that. This also applies to many working and business professionals in other verticals and professions. Put simply, you need to build confidence, stop being a wimp, and start saying “No” to pointless work.Data Scientists can become the new decision-makers at companies and should be picking their own value-added projects When a company hires a data science team, the customers of that ... 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.   Featured Resources and Technical Contributions  Key Graph Based Shortest Path Algorithms - Part 1: Dijkstra's And Bellman-Ford + Portfolio optimization with Quantum Computing Multi Gigabyte R data.table for Ohio Voter Registration/History Importance of Hyper-parameters in Model development Deep Learning from first principles in Python, R and Octave Docker in 10 minutes Scene-rendering with Google's DeepMind 5 Most Preferred Programming ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. Maybe the biggest challenge we face as a society is our ability to unlearn – to let go of – outdated concepts and beliefs in order to adopt new approaches. Our everyday lives are dominated by outdated concepts: change the oil every 3,000 miles, don’t wear white before Memorial Day, only senior management has the best ideas, don’t eat dessert until you’ve cleaned your plate, trade wars are easy to win, leeches work wonders on headaches, etc. Well, I’m going to throw down the gauntlet and challenge everyone to ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. Introduction The deployment of Machine Learning and Deep Learning algorithms on Edge devices is a complex undertaking. In this post, I list the strategies for deploying AI to Edge devices end-to-end i.e. for the full pipeline covering machine learning (building modules) and deployment (devops) I welcome your comments on additional ideas that could be included. In subsequent posts, I will elaborate these ideas in detail and ultimately, this will a free book on Data Science Central. I will take a use-case based approach i.e. each section would start with ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Janardhanan PS. Machine Learning (ML) development is an iterative process in which the accuracy of predictions made by the models is continuously improved by repeating the training and evaluation phases. In each of these iterations, certain parameters are tweaked continuously by developers. Any parameter manually selected based on learning from previous experiments qualify to be called a model hyper-parameter. These parameters represent intuitive decisions whose value cannot be estimated from data or from ML theory. The hyper-parameters are knobs that you tweak during each iteration of training a model to improve ... Read More

Feed: R-bloggers. Author: Bob Muenchen. [This article was first published on R – r4stats.com, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. By Bob Hoyt& Bob Muenchen Data science is being used in many ways to improve healthcare and reduce costs. We have written a textbook, Introduction to Biomedical Data Science, to help healthcare professionals understand the topic and to work more effectively with data scientists. The textbook content and data exercises do ... Read More

Feed: SAS Blogs. Author: Suzanne Morgen. Are you ready to get a jump start on the new year? If you’ve been wanting to brush up your SAS skills or learn something new, there’s no time like a new decade to start! SAS Press is releasing several new books in the upcoming months to help you stay on top of the latest trends and updates. Whether you are a beginner who is just starting to learn SAS or a seasoned professional, we have plenty of content to keep you at the top of your game. Here is a sneak peek at ... Read More

Feed: Radar. Author: Zan McQuade and Amanda Quinn. As we enter a new decade, we asked programming experts⁠—including several of our own O’Reilly authors and instructors⁠—for their thoughts on what’s in store for some established players and fast-growing languages. Python The biggest news this year in Python is that creator and “benevolent dictator for life” Guido van Rossum retired, leaving Python in the hands of the Python Steering Council. So far, it’s been a painless shift in power, which as Eric Matthes, author of Python Crash Course, argues, should come as no surprise, since “Guido has carried himself, and his ... Read More