Tag: data science

Feed: Featured Blog Posts - Data Science Central. Author: Sandipan Dey. In this article a few popular image processing problems along with their solutions are going to be discussed. Python image processing libraries are going to be used to solve these problems. Image Transformations and Warping 0. Display RGB image color channels in 3D A gray-scale image can be thought of a 2-D function f(x,y) of the pixel locations (x,y), that maps each pixel into its corresponding gray level (an integer in [0,255], e.g.,). For an RGB image there are 3 such functions, f_R(x,y), f_G(x.y), f_B(x.y). matplotlib’s 3-D plot functions can be used to plot each function. The following ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vibhor Nigam. This post is a token of appreciation for the amazing open source community of Data Science, to which I owe a lot of what I have learned. For last few months, I have been working on a side project of mine to develop machine learning application on streaming data. It was a great learning experience with numerous challenges and lots of learning, some of which I have tried to share in here. This post is focused on how to deploy machine learning models on streaming data and covers all ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Nishtha Singh. Technology changes on the daily basis transforming the rules like never before. Something that looked modern and fresh yesterday can appear dated seemingly overnight, and trends once dismissed as irrevocably passé can unexpectedly cycle back in vogue. Over the past few years, AI, Big Data, and such disruptive technologies have succeeded in transforming many industries already but a notable and a positive change noticeable is in the travel sector. Maybe because travel industries comprises of an enormous amount of data through online searches, analysis of consumer buying behavior but ... Read More

Feed: R-bloggers. Author: xi'an. I came across this question on X validated that wondered about one of our examples in Monte Carlo Statistical Methods. We have included a section on Laplace approximations in the Monte Carlo integration chapter, with a bit of reluctance on my side as this type of integral approximation does not directly connect to Monte Carlo methods. Even less in the case of the example as we aimed at replacing a coverage probability for a Gamma distribution with a formal Laplace approximation. Formal due to the lack of asymptotics, besides the length of the interval (a,b) which ... 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. Featured Resources and Technical Contributions  Solving Image Processing Problems with Python - Part 1 Getting Started with NLP: Simple Topic Modeling in R - Part 1 Deploying Machine Learning Models on Spark Structured Streaming  General Myths to avoid in Data Science and Machine Learning  Neural Networks from a Bayesian Perspective  Comparison of the Top Cloud APIs for Computer Vision  A Little College Sports Analysis, but ... Read More

Feed: R-bloggers. Author: Anisa Dhana. In comparison with other statistical software (e.g., SAS, STATA, and SPSS), R is the best for data visualization. Therefore, in all posts I have written for DataScience+ I take advantage of R and make plots using ggplot2 to visualize all the findings. For example, previously I plotted the percentiles of body mass index in the NHANES 2005-2014 and got exactly same results as the paper published in JAMA. In this post, I will make a map of the prevalence of Alzheimer disease mortality by the state in the USA. The Centers for Disease Control and ... Read More

Feed: R-bloggers. Author: Jozef's Rblog. In this summertime post in the case4base series, we will look at useful tools in base R, which let us profile our code without any extra packages needed to be installed. We will cover simple and easy to use speed profiling, more complex profiling of performance and memory and, as always, look at alternatives to base R as well, with a special shout out to profiling integration in RStudio. Base function system.time returns the difference between two proc.time calls within which it evaluates an expression provided as argument. The simplest usage can be seen below: ... Read More

Feed: R-bloggers. Author: Thinking inside the box. A new RcppArmadillo release 0.9.100.5.0, based on the new Armadillo release 9.100.5 from earlier today, is now on CRAN and in Debian. It once again follows our (and Conrad’s) bi-monthly release schedule. Conrad started with a new 9.100.* series a few days ago. I ran reverse-depends checks and found an issue which he promptly addressed; CRAN found another which he also very promptly addressed. It remains a true pleasure to work with such experienced professionals as Conrad (with whom I finally had a beer around the recent useR! in his home town) and ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: jennifer-clemente; Artificial Intelligence, deep learning and cognitive solutions are a big part of the future of IBM, as clients accelerate their digital transformations fueled by data. The company’s new multicloud data platform, IBM Cloud Private (ICP) for Data, is yet another step in that direction. But this isn’t just another offering aimed at anybody with the word “data” in their job title.  ICP for Data is a fully unified platform layer built within a native cloud architecture that helps companies gather vast amounts of data regardless of where it lives, ... Read More

Feed: Planet big data. Author: David Smith. A monthly roundup of news about Artificial Intelligence, Machine Learning and Data Science. This is an eclectic collection of interesting blog posts, software announcements and data applications I've noted over the past month or so. Open Source AI, ML & Data Science News ONNX Model Zoo is now available, providing a library of pre-trained state-of-the-art models in deep learning in the ONNX format. In the 2018 IEEE Spectrum Top Programming Language rankings, Python takes the top spot and R ranks #7. Julia 1.0 has been released, marking the stabilization of the scientific computing ... Read More