Tag: datasets

Feed: R-bloggers. Author: free range statistics - R. There was a flurry of activity in the last couple of days on Twitter and the blogosphere, most notably Thomas Lumley’s excellent Stats Chat, relating to whether there is a pro-government bias in surveys of New Zealand voting intention in the summer. As the analysis I’ve seen used my nzelect R package, this motivated me to update it for recent polls. The nzelect update nzelect hasn’t been updated on CRAN for some time, because about a year ago I made some major changes to the data model for the historical election results ... Read More

Feed: Alation. Author: Aaron Kalb. It’s time for a change. One of our core values here at Alation is to measure our success through customer impact. Since we launched, Alation has made it easier for data consumers to find, understand, and trust relevant datasets. Numerous studies had shown that before we introduced the first Machine Learning Data Catalog, analysts and data scientists would spend more than 80% of their time scrounging around for the right data and trying to make sense of it, instead of actually working with it. The efficiency benefits of Alation’s Find–Understand–Trust trifecta were evident, and soon ... Read More

Feed: Redis Labs. Author: Madhukar Kumar. The data landscape has grown increasingly demanding and crowded in the last few years, with many platforms competing to offer the best processing and storage options. Tech consumers expect companies to deliver high-speed data processing while simultaneously offering a variety of adaptable solutions that work with traditional applications but also built for modern architecture like microservices. Unlike a monolithic framework, a microservice structure enables companies to facilitate faster time-to-market for new applications or updates. With the lightweight design and agility of microservices, companies can allocate each individual service they offer to its own distinct ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Benjamin Waxer. In this 5 Minute Analysis we'll preprocess, map, and explore complicated sales data for liquor stores in Iowa. Then we’ll extract the relevant latitude and longitude from a problematic column of the data and discover the city with the most sales. Next we’ll filter the data to that city and prepare the data for easy loading into Business Analysis tools such as Tableau and PowerBI. Finally we’ll use our extracted location data to visualize sales within the selected city.Dataset: Iowa Liquor Sales This blog post explores and analyzes the ... Read More

Feed: R-bloggers. Author: Hugo Bowne-Anderson. Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Marco Blume, Trading Director at Pinnacle Sports. Here is the podcast link. Hugo: Hi there, Marco, and welcome to Dataframed. Marco: Yeah, hi Hugo. Thanks for having me. Hugo: Real pleasure to have you on the show and I’m actually really excited to have you here today to talk about sports betting, how data science plays a huge role in what you do as trading director at Pinnacle, with respect to sports betting. And also the fact that sports betting in your line of ... Read More

Feed: AWS Big Data Blog. Climate Change continues to have a profound effect on our quality of life. As a result, the investigation into sustainability is growing. Researchers in both the public and private sector are planning for the future by studying recorded climate history and using climate forecast models.To help explain these concepts, this post introduces the Global Historical Climatology Network Daily (GHCN-D). This registry is used by the global climate change research community. This post also provides a step-by-step demonstration of how Amazon Web Services (AWS) services improve access to this data for climate change research. Data scientists ... Read More

Feed: SAS Blogs. Author: Robert Allison. With the US census coming in 2020, I've decided to sharpen my skills at graphing census data. And today I'm working on creating a population pyramid chart to analyze the age and gender distribution. Follow along if you'd like to see how to create such a chart ... or jump to the end to see the final chart! Raw Data First, you'll need some data. I'm using the 2010 data, and hopefully the 2020 data will likely be structured very similarly. I went to the Census data page, selected the datasets link, and downloaded ... Read More

Feed: Big Data Made Simple. Author: Baiju NT. Data is power and with that power comes great responsibility. One of the biggest obstacles in data is identifying duplicates and de-duping.The aim of data-deduplication is to eliminate any redundant data in your business. Duplicates are created in all areas of your business such as the sales rep inputting a new record without checking the database first, a marketer uploading a list of potential buyers without checking if the record exists and a customer who inputs their information again as they forgot they have an account with you already.Data deduplication ensures proper ... Read More

Feed: Big Data Made Simple. Author: Amanda Peterson. Machine learning is an application of artificial intelligence that gives a system the ability to learn in real time and improve itself from experiences without being explicitly programmed. As the machine learning industry continues to advance, it’s important to continue learning about it yourself. In this article, we have listed some of the best machine learning books available for free, that you should consider.Think Stats – Probability and Statistics for ProgrammersAuthor: Allan B. Downey‘Think Stats’ is an introductory book to statistics and probability for people with a basic background in Python programming ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sean Owen. An Introduction to Bayesian Reasoning You might be using Bayesian techniques in your data science without knowing it! And if you're not, then it could enhance the power of your analysis. This blog post, part 1 of 2, will demonstrate how Bayesians employ probability distributions to add information when fitting models, and reason about uncertainty of the model's fit. Grab a coin. How fair is the coin? What is the probability p that it will land 'heads' when flipped? You flip the coin 5 times and see 2 heads ... Read More