Feed: Hortonworks Blog – Hortonworks. Author: Matt Spillar. We’ve just published our most recent case study! This story gives an in-depth look at how Pinsight Media is leveraging diverse datasets to drive new insights. Pinsight Media (Pinsight) is the mobile data company that uses verified, network-level data to fuel intelligent brand decisions. Its data management platform ingests over 60 terabytes of data coming from 65 million devices across multiple mobile network operators. Network-level data provides right-time advertising, capturing those with the highest propensity to respond. The company required an agile, scalable platform to help address the challenges of volume, veracity, velocity, and variety ... Read More

Feed: All - O'Reilly Media. Author: Ben Lorica. Building blocks (source: Pixabay) To get started with Ray, attend upcoming three-hour tutorials on “Building reinforcement learning applications with Ray” at the Artificial Intelligence conference: in San Francisco (September 5, 2018) and in London (October 9, 2018). Machine learning adoption is accelerating due to the growing number of large labeled data sets, languages aimed at data scientists (R, Julia, Python), frameworks (scikit-learn, PyTorch, TensorFlow, etc.), and tools for building infrastructure to support end-to-end applications. While some interesting applications of unsupervised learning are beginning to emerge, many current machine learning applications rely on ... Read More

Feed: All - O'Reilly Media. Author: Steve Souders. This is an excerpt from "High Speed UX." Watch the full video on O'Reilly's online learning platform. In this video segment, Steve Souders aims to bring designers and developers closer together with a few best practices for delivering a fast, enjoyable user experience. Watch the full video on O'Reilly's online learning platform. Article image: Yin yang (source: Pixabay). Steve Souders works at SpeedCurve on the interplay between performance and design. He previously served as Google’s head performance engineer, chief performance Yahoo!, and as chief performance officer at Fastly. Steve has pioneered much ... Read More

Feed: All - O'Reilly Media. Author: Douwe Osinga. Eye (source: Pixabay) This post is adapted from Douwe Osinga’s book "Deep Learning Cookbook." Read the full book on O’Reilly’s online learning platform. In the last decade or so, computer vision has made tremendous strides forward, mostly because of developments in deep learning. It is not just that we have new and better algorithms—digital cameras and the web have provided us with a near infinite set of training data. And maybe even more importantly, graphics cards developed for computer gaming turn out to have super computer powers when it comes to training ... Read More

Feed: SAS Blogs. Author: Meredith Rakowski. My “why” has always been my animals. They are the reason I drag myself out of bed every morning before the sun comes up to feed, water, and check them over before heading to school. And once there, my “why” becomes my job as I share my passion for animals with young minds. Because the material is so close to our hearts, Career and Technical Education teachers strive to convey our knowledge in unique ways. Many CTE courses are built around hands-on, experiential learning. At their core, these courses are meant to prepare students ... Read More

Feed: The Information Lab. Author: David Sanchez Martin. 15 August, 2018 | David Sánchez Martín Pascal’s Triangle – Alteryx Python SDK The original version of this article with working code is here . After a couple of posts (I & II) getting my feet wet with the Python SDK module for Alteryx I finally get to build a tool that actually uses some code: The Pascal’s Triangle generator Following the original recipe, I duplicated a sample folder, renamed the files, removed most of the superfluous code, added the pieces I needed and, finally, connected my code with the AyxPlugin. All ... Read More

Feed: Neo4j Graph Database Platform. Author: Bryce Merkl Sasaki. Languages (the natural, human kind) shape how you view the world.From color to time to gender relations, there’s no escaping how language limits (or expands) your worldview. Words are the categories and labels that we use to process and understand reality – and then to communicate that understanding to others.So when it comes to analyzing and describing data (a subset of reality), language matters.Just like their natural counterparts, technical languages shape how you understand and process your data. If a given programming language or query language doesn’t have a label or ... Read More

Feed: R-bloggers. Author: rOpenSci - open tools for open science. This week version 2.0 of the mongolite package has been released to CRAN. Major new features in this release include support for MongoDB 4.0, GridFS, running database commands, and connection pooling. Mongolite is primarily an easy-to-use client to get data in and out of MongoDB. However it supports increasingly many advanced features like aggregation, indexing, map-reduce, streaming, encryption, and enterprise authentication. The mongolite user manual provides a great introduction with details and worked examples. GridFS Support! New in version 2.0 is support for the MongoDB GridFS system. A GridFS is ... Read More

Feed: R-bloggers. Author: Mic. This is a short post following the previous one (PCA revisited). In this post I’m going to apply PCA to a toy problem: the classification of faces. Again I’ll be working on the Olivetti faces dataset. Please visit the previous post PCA revisited to read how to download it. The goal of this post is to fit a simple classification model to predict, given an image, the label to which it belongs. I’m goint to fit two support vector machine models and then compare their accuracy. The The first model uses as input data the raw ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: jay-limburn; Data can be an organization’s most valued asset, providing insights that help strengthen business. Knowing what works and what does not can help you invest more resources in what would work in the future.But there are two main challenges that might impede you from realizing the true value of your data and slowing your journey to adopting artificial intelligence (AI). Challenge 1: Inefficient data management The first challenge is the inefficiency in managing all the disparate data that flows through your enterprise. You need to ensure a fluid ... Read More