fbpx

  • Warning: Invalid argument supplied for foreach() in /home/customer/www/opendatascience.com/public_html/wp-includes/nav-menu.php on line 95

    Warning: array_merge(): Expected parameter 2 to be an array, null given in /home/customer/www/opendatascience.com/public_html/wp-includes/nav-menu.php on line 102
Data Wrangling
Why Blockchain Will Improve Your Big Data

Why Blockchain Will Improve Your Big Data

Business + ManagementData WranglingDS @ ScaleModelingTechnologyTools & LanguagesBig Dataposted by Mark van Rijmenam October 17, 2017

The rise of cloud storage has helped companies collect and manage massive amounts of data. Data comes from corporate systems, Internet of Things objects and unstructured sources like online forums. New analytics tools like Hadoop help companies make sense of that data. Yet simply having data... Read more
Custom Level Coding in vtreat

Custom Level Coding in vtreat

Data WranglingModelingRTools & Languagesposted by John Mount October 13, 2017

One of the services that the R package vtreat provides is level coding (what we sometimes call impact coding): converting the levels of a categorical variable to a meaningful and concise single numeric variable, rather than coding them as indicator variables (AKA “one-hot encoding”). Level coding can be computationally and statistically preferable to... Read more

Using The Newspaper Library to Scrape News Articles

Data WranglingModelingNLP/Text AnalyticsToolsTools & LanguagesNatural Language Processingposted by George McIntire, ODSC October 12, 2017

This post is the first of a two-part series in which we apply NLP techniques to analyze articles about big data, data science, and AI. If you are tired of the hassles of web scraping, then this post might be just for you. I occasionally web scrape news... Read more
Firing on All Cylinders: The 2017 Big Data Landscape, part 2

Firing on All Cylinders: The 2017 Big Data Landscape, part 2

Data WranglingDS @ ScaleModelingTools & Languagesposted by Matt Turck October 8, 2017

A walk through the 2017 Data Ecosystem Landscape INFRASTRUCTURE A lot of themes from last year have continued to play out, such as the ever-increasing importance of streaming, with Spark reigning supreme for now, with interesting contenders such as Flink emerging. In addition, a few interesting themes have kept... Read more
Datasets for Building a Data Analysis Portfolio

Datasets for Building a Data Analysis Portfolio

BlogData WranglingDS @ ScaleModelingTools & LanguagesDatasetposted by Ari Lamstein October 1, 2017

I recently had the pleasure of attending the 2017 Association of Public Data Users (APDU) Conference. My favorite part of the conference was talking to people who work with federal data on a daily basis. Overall I found people to be passionate about their work and eager... Read more
Beyond Computational Reproducibility, let us Aim for Reusability

Beyond Computational Reproducibility, let us Aim for Reusability

Data WranglingModelingResearchposted by Gael Varoquaux September 30, 2017

Scientific progress calls for reproducing results. Due to limited resources, this is difficult even in computational sciences. Yet, reproducibility is only a means to an end. It is not enough by itself to enable new scientific results. Rather, new discoveries must build on reuse and modification... Read more

Firing on All Cylinders: The 2017 Big Data Landscape, part 1

BlogData WranglingDS @ ScaleModelingTools & Languagesposted by Matt Turck September 26, 2017

It feels good to be a data geek in 2017. Last year, we asked “Is Big Data Still a Thing?”, observing that since Big Data is largely “plumbing”, it has been subject to enterprise adoption cycles that are much slower than the hype cycle. As a result,... Read more
Web Scraping Indeed for Key Data Science Job Skills

Web Scraping Indeed for Key Data Science Job Skills

Career InsightsData WranglingModelingResearchData Science Jobsposted by Jesse Steinweg-Woods September 20, 2017

Editor’s Note: Check out our 2017 State of Data Science Jobs Report to compare stats, sentiments, and POVs. *available in Spanish   As many of you probably know, being a data scientist requires a large skill set . . . Read more

Easy Access to All Points of Interest Data

BlogData VisualizationData WranglingModelingposted by August 8, 2017

Scraping OpenStreetMap and exploring POI in Cloudant and Jupyter Notebooks When working with data, the format of the raw data is not always user-friendly. For instance, the format could be one large binary file, or the data could spread across hundreds of text files. An easy... Read more

Conversion rates — you are (most likely) computing them wrong

BlogData Wranglingposted by Erik Bernhardsson July 13, 2017

How hard can it be to compute conversion rate? Take the total number of users that converted and divide them with the total number of users. Done. Except… it’s a lot more complicated when you have any sort of significant time lag. Prelude — a story Fresh out... Read more
Copyright © 2023 Open Data Science. All rights reserved.